Analyze The Evolution Of Social Media Standards And Practices And How It Relates To The Potential Need For Regulation Of Social Media

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Many people get all or most of their news from social media. For this project, we are going to be analyzing the content of several social media sites from major news sources, paying particular attention to social media standards, practices, and regulation.

Where do you get your news? Start by going to one major news site’s FACEBOOK page (CNN, MSNBC, FOX, etc.) Try another different news site’s TWITTER feed, and third choose another social media site such as Reddit, Pinterest, or another (preferably one you use, if there is one).

Analyze the sites in a 3-5 page total paper. In your analysis, be sure to include the following:

  • General introduction to your thoughts on the social media you studied
  • Several social media practices you observed (e.g., what gets the most interaction?)
  • Examples of regulation of social media and discussion of such regulation (Is it good, bad, or indifferent? How could circumstances change the situation?)
  • Analysis of ethical concerns (e.g., can you see examples of bias?)
  • What is the culture of each site – how do users seem to respond to questionable items? (Is racism or open mocking ignored or pursued?)
  • Conclusion of your findings

Determining A Diagnosis

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Review the diagnostic criteria on pages 99-100; 160-161; 561-562 of  the DSM-5.

A counselor’s own perception of psychopathology is extremely  important in the diagnostic process.

Using the case study of “Tina”, write a 500-750 word essay  in which you examine your thought process about her presenting issues.  Include the following in your paper:

  1. Discuss the historic and cross-cultural perspectives of    psychopathology that could potential impact the diagnosis and    treatment of Tina.
  2. After reviewing the several diagnoses    that could pertain to Tina from the latest version of the DSM, what    is your diagnostic impression?
  3. Substantiate your diagnostic    impression with appropriate criteria from the current version of the  DSM.
  4. Discuss how historic misconceptions of psychopathology    could potentially impact the treatment of this client. As part of    this discussion, you may include a diagnosis, any referrals that you    would make, and a general course of treatment.
  5. Include at    least five scholarly references in addition to the textbook in    your paper.

Case Study: Tina Tina is a 17-year-old Navajo female who is brought into a counselor’s office for symptoms of depression; her family has noticed that she is more withdrawn than usual and she is often observed crying and talking to herself. Through the intake interview, the counselor learns that Tina hears voices daily that command her to perform certain acts of hygiene (showering, combing her hair, etc.). She further reveals that she believes these voices to be the result of witchcraft that her boyfriend is using to control her. Tina also states that she has used methamphetamines heavily for the past several months. She and her mother ask the counselor to work with Tina for the depression, but claim that they wish to see a medicine man for hearing voices. Where does the counselor begin with this client? Tina is clearly demonstrating symptoms of psychoses, yet it is difficult to determine what has caused them. Is she experiencing a severe depressive episode with psychotic features? Have the voices been induced by excessive drug use? Alternatively, should the counselor take into account the cultural acceptance of witchcraft and let the medicine man exclusively treat Tina? This case study is but one example of the way different cultures deviate in concept of mental illness as it presents itself in the counselor’s office. Viewing clients as devoid of their cultural backgrounds because notions of health and wellness differ greatly by who is defining them are unethical and unwise. In order to be as receptive as possible to a client’s position, counselors must constantly deconstruct and be aware of their own beliefs regarding psychopathology. This process of exploring a belief system has been given many names, one of which is social constructionism (Lemma, 2011). Social constructionism is the concept that reality is formed and defined by the individual experience of it; the perceptions of any given society are constantly in flux as trends and knowledge shifts. As such, the concept of psychology changes to meet the needs of each given culture. Ruder & Guterman (2007) state that “social constructionism is, itself, a social construction that is always changing and subject to reconstruction” (p. 387).

References   Rudes, J. & Guterman, J. (2007). The value of social constructionism for the counseling profession: A reply to Hansen. Journal of Counseling & Development,85(4), 387-392

 

· What role did culture play in selecting materials for use in play therapy?

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Unit 10A Discussion 1 & 2? $30.00 Due (SAT) 9/08/2018.

Unit 10 Discussion 1

Consulting and Collaborating

Examine Table 16.1, Mental Health Consultation, in Counseling Children, page 516. Using the categories presented there, how would you classify the type of consultation described in Ackman’s 2012 article, “Helping the Helpers”? Provide a rationale for your response.

If you were to join the consultation team for the project serving the mental health needs of children and their mothers, what additional principles of consultation would you see as priorities? Which aspects from the models described in Chapter 16 of Counseling Children apply to this situation? Offer your rationale for why you would make these principles your top priorities, citing this Unit’s readings to support your views.

Resources

· Discussion Participation Scoring Guide.

· Helping the Helpers: Consultation to Childcare Staff Using Psychoanalytically Informed Developmental Concepts.

Unit 10 Discussion 2[u10d2] Unit 10 Discussion 2

Designing the Office

Congratulations! After reviewing your materials, the Middle Valley Child Consortium has decided to hire you for their Middle Valley Child and Adolescent Counseling Project. They have offered you the chance to choose the setting for your counseling work and they’ve given you a budget for materials and reference books.

Part 1: Choosing Materials for Child and Adolescent Counseling

After completing the interactive media, “Choosing Materials for Play Therapy,” and reading the article you chose that illustrates using expressive techniques with families with small children (Wehrman and Field’s 2013 article, “Play-Based Activities in Family Counseling”) or with adolescents in groups (Swank and Lenes’s 2013 article, “An Exploratory Inquiry of Sandtray Group Experiences With Adolescent Females in an Alternative School”), describe the following:

· What practice setting did you choose for your hypothetical work with children and adolescents?

· What materials did you choose for your setting, and why?

· What role did culture play in selecting materials for use in play therapy?

Part 2: Choosing Books to Expand your Knowledge

At this point in the course, you’ve probably identified a particular area of professional interest. Imagine you’ve been given a blank check to purchase any three books for your professional library. What will you choose?

· First, clearly identify your area of interest and briefly explain why you want to learn more about it.

· Review the list of optional books in this course and decide upon three books that are in a particular area of interest you.

· List the references for your three books.

· For each book, offer a brief rationale for that explains how this resource will enhance your knowledge in an area where you want to add specialized knowledge about child or adolescent counseling.

Part 3: Reflection on the Exercise

How has this exercise influenced your ideas about child and adolescent therapy, and what is involved in being an effective therapist for young people?

Resources

· Discussion Participation Scoring Guide.

· Choosing Materials for Play Therapy.

· Play-Based Activities in Family Counseling.

· An Exploratory Inquiry of Sandtray Group Experiences With Adolescent Females in an Alternative School.

· Finally, consultee-centered administrative consultation focuses on remedying difficulties among consultees that interfere with their abilities to perform their work. These problems may be the individual difficulties noted in consultee-centered case consultation or may be the result of poor leadership, authority difficulties, communication blocks, and other group problems. Table 16.1 provides a comparison of these four types of consultation.

TABLE 16-1: MENTAL HEALTH CONSULTATION

  Client-centered Case Consultation Consultee-centered Case Consultation Program-centered Administrative Consultation Consultee-centered Administrative Consultation
Focus Client-centered case consultation focuses on developing a plan that will help a specific client. Consultee-centered case consultation focuses on improvement of the consultee’s professional functioning in relation to specific cases. Program-centered administrative consultation focuses on improvement of programs or policies. Consultee-centered administrative consultation focuses on improvement of consultee’s professional functioning in relation to specific programs or policies.
Goal To advise the consultee regarding client treatment. To educate consultee using his or her problems with the client as a lever. To help develop a new program or policy or improve an existing one. To help consultee improve problem-solving skills in dealing with current organizational problems.
Example School psychologist called in to diagnose a student’s reading problem. School counselor asks for help in dealing with students’ drug-related problems. Nursing home director requests help in developing staff orientation program. Police chief asks for help in developing ongoing program to deal with interpersonal problems between veteran and new officers.
Consultant’s Role and Responsibilities Usually meets with consultee’s client to help diagnose problem. Never, or rarely, meets with consultee’s client. Meets with groups and individuals in an attempt to accurately assess problems. Meets with groups and individuals in an attempt to help them develop their problem-solving skills.
  Is responsible for assessing problem and prescribing course of action. Must be able to recognize source of consultee’s difficulties and deal with them indirectly. Is responsible for correctly assessing problem and providing a plan for administrative action. Must be able to recognize source of organizational difficulty and serve as catalyst for action by administrators.
From Brown, D., Pryzwansky, W. B., & Schulte A. C. (2006). Psychological consultation: Introduction to theory practice (6th ed., p. 32). Boston, MA: Allyn and Bacon. Copyright 2006 by Allyn and Bacon. Reprinted with permission.

Across the different types of mental health consultation, consultants consider these fundamental assumptions. Both characteristics of the consultee and the environment must be considered. Consultee’s beliefs, feelings, and attitudes impact behavior. Furthermore problems do not reside completely within the client but also at several levels within and outside of the organization. Other assumptions rest on the idea that technical expertise must be incorporated into intervention design. That belief recognizes that the norms, roles, language, and body of knowledge of the profession combine for the unique aspects of the context of the consultation. Furthermore, the responsibility for action belongs to the consultee. That practice promotes learning and generalization to other situations for the consultee. Caplan and Caplan (1999) explain that mental health consultation provides a supplement to other problem-solving mechanisms within an organization and that consultee attitudes and affect cannot be addressed directly—that would upset the working relationship in many ways (Brown et al., 2011). Sandoval (2014) has compiled an excellent volume about the application of consultee-centered consultation in schools.

Knotek and Sandoval (2003) pointed to a new definition of consultee-centered consultation that identifies the goals as a joint development of new ways to see the work problem. The process includes orderly reflection, generating hypothesis, and exchanging information. The relationship between consultant and consultee is supportive and equal. The goal of the relationship is changing the consultee’s understanding of the situation. The consultant helps the consultee think differently by using a range of techniques (Caplan & Caplan-Moskovich, 2004), with dialogue being used to explore the consultee’s view of the problem, introduce alternative viewpoints or new information, or reframing the problem to a solution focus. Nonetheless, the consultee is free to accept or reject the consultant’s ideas (Brown et al., 2011).

Another modification of mental health consultation is the ecological approach in which the consultant sees the client system as the source of difficulties between the individual’s ability and the demands of the environment (Gutkin, 2009, 2012). This approach involves three premises. The first assumption is that each setting has finite resources for maintaining and developing itself. Next, the model posits that in an adaptive environment the members have a variety of competencies. Therefore, the goal of intervention is to activate and develop resources. The ecological perspective focuses on consultation that cultivates opportunities to build competencies for self-development (Dougherty, 2013).

BEHAVIORAL AND COGNITIVE-BEHAVIORAL CONSULTATION

For school or mental health counselors interested in a more structured model of consultation, behavioral consultation may be appealing. This approach to consultation requires a deep understanding of behavioral theory and practice, especially Bandura’s social learning theory (Bandura, 1977). The foundation of behavioral consultation is that behavior is observable and can be modified through the use of learning principles.

Kratochwill, Elliott, and Callan-Stoiber (2002) outlined behavioral consultation and therapy as the application of systems theory and principles of learning a problem-solving process. The consultant gathers information from the consultee and then defines the problem in concrete, behavioral terms, as well as identifying the environmental conditions that maintain it. The consultant tries to help the consultee solve the problem by changing either the client’s or consultee’s behavior or the system in which the client and the consultee exist. Dougherty (2013) and Scott, Royal, and Kissinger (2015) detail the sequence of behavioral consultation as follows:

· 1. Problem identification: After a detailed analysis is performed, the problem is formulated in succinct, behavioral terms.

· 2. Problem analysis: A functional analysis of the problem is studied within its framework; antecedents and consequences are identified as well as task demands (cognitive, time, educational, and others).

· 3. Selection of a target behavior: The focus of the consultation is chosen.

· 4. Behavior objectives: Specific goals of the intervention are generated.

· 5. Plan design and implementation: A behavioral plan is developed and applied.

· 6. Evaluation of the behavioral change program: Measurement of behavioral outcomes in relation to goals established occurs.

The guiding principles of this model are the scientific perspective of using evidence-based practices, an orientation to the present, and the use of behavior change processes of operant conditioning—reinforcement, punishment, and shaping of behavior. Interventions begin with the agreement of consultant and consultee on a behavioral objective with one of three broad goals—reducing inappropriate behavior, increasing appropriate behavior, or eliminating an identified behavior. Consultant and consultee collaborate to change behavior. Intervention strategies, such as those described by social learning theory and cognitivebehavioral theory, also can be applied in the consultative setting to address either the antecedent or the consequence of the identified behavior. The choice of the intervention would be based on the one best suited to the knowledge, skills, and goals of the consultee (Scott et al., 2015).

MacLeod, Jones, Somers, and Havey (2001) have investigated the effectiveness of school-based behavioral consultation. Their findings support the importance of consultant skills and the quality of consultation in generating successful outcomes. Wagner (2008) identified behavioral consultation as one of the two most common methods to work with parents. The consultant promotes behavior change by closely examining the environmental antecedents and consequences of the child’s actions. Parents learn to observe and monitor the behaviors also and then apply behavioral techniques to modify the actions. Operant conditioning, which includes the use of positive reinforcement, punishment, and extinction, is the technique parents are taught. Danforth (1998) provided a Behavior Management Flow Chart, which gives parents a step-by-step decision-making process to respond to their child’s behavior.

Brown, Pryzwansky, and Schulte (2006) have developed general interview guidelines for behavioral noncrisis and crisis consulting. The consultant in a noncrisis situation (developmental interview) focuses on the following tasks:

· 1. Establishing clear general objectives

· 2. Reaching agreement with the consultee in the relationship between general objectives and more specific ones

· 3. Generating clearly defined, prioritized performance objectives with the consultee

· 4. Deciding how accomplishment of performance objectives will be assessed and recorded

· 5. Deciding on follow-up meetings

In a crisis or problem-centered interview, the outline focuses on the following tasks:

· 1. Identifying and describing problematic behavior(s) by collecting data from several sources concerning the nature of the problem

· 2. Determining the conditions under which these behaviors occur, their antecedents, and their consequences; the consultant and consultee analyze either the setting or interpersonal factors that contribute to the problem or the client’s skill deficits

· 3. Deciding on assessment procedures; the consultant and consultee design a plan to deal with the problem by identifying objectives, selecting behavioral interventions, considering barriers to overcome, and evaluating progress

· 4. Scheduling future meetings (Brown et al., 2006, pp. 52–53)

MacLeod et al. (2001) conclude that intervention planning was positively correlated to student outcome. A step-by-step plan, adhering to the treatment plan, and the comparison of baseline and treatment data all related to student behavioral change.

Consultants who use the cognitive-behavioral consultation approach also rely on collaboration and shared problem solving. Those consultants believe that both internal and external factors influence behavior. Antecedents to behavior may be complicated by cognitive, environmental, biological, and cultural factors. They concur that behavior has a purpose but caution that a person may not immediately know that actual purpose.

In cognitive-behavioral consultation, the consultee identifies the problem behavior or the absence of an expected behavior. The problem identification moves into a detailed description of observable, measurable behavior. A functional behavioral assessment involves identifying the cognitive, emotional, and contextual data that might be used to help select appropriate interventions. Scatter plots might be used for tracing behavior as well as personal interviews and other means of compiling a complete picture of the behavior. Chosen intervention should be simple and nonintrusive and closely monitored for effectiveness. Observing and assessing the impact of the intervention focuses on the accuracy and efficacy of the treatment (Scott et al., 2015).

SOLUTION-FOCUSED CONSULTEE-CENTERED CONSULTATION

The models presented earlier are based on a philosophy known as modernist. That knowledge base assumes that reality is a knowable, objective reality. Those philosophers contend that only the scientific method of research identifies and verifies new knowledge. In addition, they presume that human behavior can be measured and quantified in meaningful ways. Cause-and-effect relationships exist and are discoverable through appropriate research methods. Accordingly, the context in which people exist are considered either neutral or unimportant.

On the other hand, social constructivism, a postmodern philosophy, is based on the premise that a person cannot be separated from context, people must be studied in their environments. These theorists repudiate the idea that cause-and-effect relationships can be inferred and that the only legitimate source of knowledge about a person is the subjective frame of reference of that individual. Finally, these thinkers propose that the acquisition of knowledge occurs through social interaction.

This approach to consultation borrows significantly from the work of Steve de Shazer (1985) and his wife Insoo Kim Berg that was discussed in Chapter 10. In this approach to consultation, consultant works to understand how or what the consultee identifies as the problem and potential solution. Using brief solution-focused interventions, such as finding exceptions, the miracle question, scaling questions, and understanding the clients’ stories based on their perceptions, the consultant structures the process mirroring the therapeutic one.

During the first session, the consultant helps the consultee reframe the problem in manageable ways. The strengths of the consultee are identified and the consultant may distinguish themselves as coaches or facilitators of the problem-solving process. Problem identification begins with the question “what can I do for you today?” which quickly moves to forming a goal as well as scaling the problem. Solution-finding starts when the problem is identified and continues as consultant and consultee consider what has been tried and how that action has worked previously—exceptions to the problem help the dyad build a way to another outcome to the problem. Kahn (2000) presents a case study of this model used with a teacher in a middle school.

PROCESS CONSULTATION

Edward Schein (1999) has proposed a model of consultation he labels process consultation. He considers this approach to consultation as a skill. He emphasizes the interest in how things happen between people rather than what is actually done. More specifically, he defines process consultation as a “set of activities on the part of the consultant which help the (consultee) to perceive, understand, and act upon process events which occur in the (consultee’s) environment” (Schein, 1988, p. 11).

This type of consultation focuses on the ways problems are solved and on the system in which the problems occur. The consultant and consultee examine six different areas: (1) communication patterns, (2) group member roles, (3) group problem solving and decision making, (4) group norms and growth, (5) leadership and authority, and (6) intergroup cooperation and competition. The consultant may operate as a catalyst in helping the consultee find a solution or as a facilitator who aids the consultee through a problem-solving process (Dougherty, 2013).

Harrison (2004) explains three strategic goals of process consultation. The first is to encourage a situation in which the client will ask for help. The next is to diagnose or create a situation so that information will surface and people understand better what is happening. The third goal is to build a team or create an environment in which the client will take responsibility for the problem and the solution. To accomplish these broad goals, Schein (1999) outlines these principles that can guide any consultation approach:

· 1. Constantly try to be helpful.

· 2. Stay in touch with reality by being alert to what is going on with you, with the situation, and in the consultee and client system.

Analyze the computation, application, strengths, and limitations of various statistical tests.

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For this assessment, you will complete an SPSS data analysis report using t-test output for assigned variables.

You will review the theory, logic, and application of t tests. The t test is a basic inferential statistic often reported in psychological research. You will discover that t tests, as well as analysis of variance (ANOVA), compare group means on some quantitative outcome variable.

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By successfully completing this assessment, you will demonstrate your proficiency in the following course competencies and assessment criteria:

  • Competency 1: Analyze the computation, application, strengths, and limitations of various statistical tests.
    • Develop a conclusion that includes strengths and limitations of an independent-samples t test.
  • Competency 2: Analyze the decision-making process of data analysis.
    • Analyze the assumptions of the independent-samples t test.
  • Competency 3: Apply knowledge of hypothesis testing.
    • Develop a research question, null hypothesis, alternative hypothesis, and alpha level.
  • Competency 4: Interpret the results of statistical analyses.
    • Interpret the output of the independent-samples t test.
  • Competency 5: Apply a statistical program’s procedure to data.
    • Apply the appropriate SPSS procedures to check assumptions and calculate the independent-samples t test to generate relevant output.
  • Competency 6: Apply the results of statistical analyses (your own or others) to your field of interest or career.
    • Develop a context for the data set, including a definition of required variables and scales of measurement.
  • Competency 7: Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study.
    • Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study.

     

Read Assessment 3 Context [DOC] for important information on the following topics:

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  • Logic of the t test.
  • Assumptions of the t test.
  • Hypothesis testing for a t test.
  • Effect size for a t test.
  • Testing assumptions: The Shapiro-Wilk test and Levene’s test.
  • Proper reporting of the independent-samples t test.
  • t, degrees of freedom, and t value.
  • Probability value.
  • Effect size.

 

Read Assessment 3 Context (linked in the Resources) to learn about the concepts used in this assessment.

You will use the following resources for this assessment. They are linked in the Resources.

  • Complete this assessment using the DAA Template.
  • Read the SPSS Data Analysis Report Guidelines for a more complete understanding of the DAA Template and how to format and organize your assessment.
  • Refer to IBM SPSS Step-By-Step Instructions: t Tests for additional information on using SPSS for this assessment.
  • If necessary, review the Copy/Export Output Instructions to refresh your memory on how to perform these tasks. As with your previous assessments, your submission should be narrative with supporting statistical output (table and graphs) integrated into the narrative in the appropriate place (not all at the end of the document).

You will analyze the following variables in the grades.sav data set:

  • gender.
  • gpa.

Step 1: Write Section 1 of the DAA

  • Provide a context of the grades.sav data set.
  • Include a definition of the specified variables (predictor, outcome) and corresponding scales of measurement.
  • Specify the sample size of the data set.

Step 2: Write Section 2 of the DAA

  • Analyze the assumptions of the t test.
  • Paste the SPSS histogram output for gpa and discuss your visual interpretations.
  • Paste SPSS descriptives output showing skewness and kurtosis values for gpa and interpret them.
  • Paste SPSS output for the Shapiro-Wilk test of gpa and interpret it.
  • Report the results of the Levene’s test and interpret it.
  • Summarize whether or not the assumptions of the t test are met.

Step 3: Write Section 3 of the DAA

  • Specify a research question related to gender and gpa.
  • Articulate the null hypothesis and alternative hypothesis.
  • Specify the alpha level.

Step 4: Write Section 4 of the DAA

  • Paste the SPSS output of the t test.
  • Report the results of the SPSS output using proper APA guidelines. Include the following:
    • t.
    • Degrees of freedom.
    • t value.
    • p value.
    • Effect size.
    • Interpretation of effect size.
    • Means and standard deviations for each group. Mean difference.
    • Interpret the results against the null hypothesis.

Step 5: Write Section 5 of the DAA

  • Discuss the implications of this t test as it relates to the research question.
  • Conclude with an analysis of the strengths and limitations of t-test analysis.

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    Assessment 3 Context

    You will review the theory, logic, and application of t-tests. The t-test is a basic inferential statistic often reported in psychological research. You will discover that t-tests, as well as analysis of variance (ANOVA), compare group means on some quantitative outcome variable.

    Recall that null hypothesis tests are of two types: (1) differences between group means and (2) association between variables. In both cases there is a null hypothesis and an alternative hypothesis. In the group means test, the null hypothesis is that the two groups have equal means, and the alternative hypothesis is that the two groups do not have equal means. In the association between variables type of test, the null hypothesis is that the correlation coefficient between the two variables is zero, and the alternative hypothesis is that the correlation coefficient is not zero.

    Notice in each case that the hypotheses are mutually exclusive. If the null is false, the alternative must be true. The purpose of null hypothesis statistical tests is generally to show that the null has a low probability of being true (the p value is less than .05) – low enough that the researcher can legitimately claim it is false. The reason this is done is to support the allegation that the alternative hypothesis is true.

    In this context you will be studying the details of the first type of test. This is the test of difference between group means. In variations on this model, the two groups can actually be the same people under different conditions, or one of the groups may be assigned a fixed theoretical value. The main idea is that two mean values are being compared. The two groups each have an average score or mean on some variable. The null hypothesis is that the difference between the means is zero. The alternative hypothesis is that the difference between the means is not zero. Notice that if the null is false, the alternative must be true. It is first instructive to consider some of the details of groups. Means, and difference between them.

    Null Hypothesis Significance Test

    The most common forms of the Null Hypothesis Significance Test (NHST) are three types of t tests, and the test of significance of a correlation. The NHST also extends to more complex tests, such as ANOVA, which will be discussed separately. Below, the null hypothesis and the alternative hypothesis are given for each of the following tests. It would be a valuable use of your time to commit the information below to memory. Once this is done, then when we refer to the tests later, you will have some structure to make sense of the more detailed explanations.

    1. One-sample t test: The question in this test is whether a single sample group mean is significantly different from some stated or fixed theoretical value – the fixed value is called a parameter.

    · Null Hypothesis: The difference between the sample group mean and the fixed value is zero in the population.

    · Alternative hypothesis: The difference between the sample group mean and the fixed value is NOT zero in the population.

    2. Dependent samples t test (also known as correlated groups t or repeated measures t): The question in this test is whether two scores for each participant differ significantly. It is actually a special case of the one-sample test, where each person’s score is the difference between his or her two original scores (difference scores). If there is no significant difference in the population, then the mean population difference score is zero (the fixed value).

    · Null Hypothesis: The mean difference between the two scores for each participant is zero in the population.

    · Alternative hypothesis: The mean difference between the two scores for each participant is NOT zero in the population

    3. Independent samples t test (two independent groups): The question in this test is whether or not two group means are from the same population, or from populations with different means.

    · Null Hypothesis: The difference between the two group’s means is zero in the population, or the two groups are from the same population.

    · Alternative hypothesis: The difference between the two group’s means is NOT zero in the population, or the two groups are from different populations.

    Logic of the t-Test

    Imagine that a school psychologist compares the mean IQ scores of Class A versus Class B. The mean IQ for Class A is 102.0 and the mean IQ for Class B is 105.0. Is there a significant difference in mean IQ between Class A and Class B?

    To answer this question, the school psychologist conducts an independent samples t-test. The independent samples t-test compares two group means in a between-subjects (between-S) design. In this between-S design, participants in two independent groups are measured only once on some outcome variable. By contrast, a paired samples t-test compares group means in a within-subjects (within-S) design for one group. Each participant is measured twice on some outcome variable, such as a pretest-posttest design. For example, a school psychologist could measure self-esteem for a class of students prior to taking a public speaking course (pretest) and then measure self-esteem again after completing the public speaking course (posttest). The paired samples t-test determines if there is a significant difference in mean scores from the pretest to the posttest.

    Focus on the logic and application of the independent samples t-test. There are two variables in an independent samples t-test: the predictor variable (X) and the outcome variable (Y). The predictor variable must be dichotomous, meaning that it can only have two values (for example, male = 1; female = 2). Notice this is nominal level variable. The outcome variable must be at the interval level or above (ratio). Group membership is mutually exclusive. In nonexperimental designs, group membership is based on some naturally occurring characteristic of a group (for example, gender). In experimental designs, participants are randomly assigned to one of two group conditions (for example, treatment group = 1; control group = 2). In contrast to the dichotomous (nominal) predictor variable, the outcome variable must be quantitative to calculate a group mean (for example, mean IQ score, mean heart rate score).

    Assumptions of the t-Test

    All inferential statistics, including the independent samples t-test, operate under assumptions checked prior to calculating the t-test in SPSS. Violations of assumptions can lead to erroneous inferences regarding a null hypothesis. The first assumption is independence of observations. For predictor variable X in an independent samples t-test, participants are assigned to one and only one “condition” or “level,” such as a treatment group or control group. This assumption is not statistical in nature; it is controlled by proper research procedures that maintain independence of observations.

    The second assumption is that outcome variable Y is quantitative and normally distributed. This assumption is checked by a visual inspection of the Y histogram and calculation of skewness and kurtosis values. A researcher may also conduct a Shapiro-Wilk test in SPSS to check whether a distribution is significantly different from normal. The null hypothesis of the ShapiroWilk test is that the distribution is normal. If the Shapiro-Wilk test is significant, then the normality assumption is violated. In other words, a researcher wants the Shapiro-Wilk test to not be significant at p < .05.

    The third assumption is referred to as the homogeneity of variance assumption. Ideally, the amount of variance in Y scores is approximately equal for group 1 and group 2. This assumption is checked in SPSS with the Levene test. The null hypothesis of the Levene test is that group variances are equal. If the Levene test is significant, then the homogeneity assumption is violated. In other words, a researcher wants the Levene test to not be significant at p < .05.

    SPSS output for the t-test provides two versions of the t-test: “Equal variances assumed” and “Equal variances not assumed.” If the Levene test is not significant, researchers report the “Equal variances assumed” version of the t-test. If the Levene test is significant, researchers report the more conservative “Equal variances not assumed” calculation of the t-test in the second row of the output table.

    Hypothesis Testing for a t-Test

    The null hypothesis for a t-test predicts no significant difference in population means, or H0: µ1 = µ2. A directional alternative hypothesis for a t-test is that the population means differ in a specific direction, such as H1: µ1 > µ2 or H1: µ1 < µ2. A non-directional alternative hypothesis simply predicts that the population means differ, but it does not stipulate which population mean is significantly greater (H1: µ1 ≠ µ2). For t-tests, the standard alpha level for rejecting the null hypothesis is set to .05. SPSS output for a t-test showing a p value of less than indicates that the null hypothesis should be rejected; there is a significant difference in population means. A p value greater than .05 indicates that the null hypothesis should not be rejected; there is not a significant difference in population means.

    Effect Size for a t-Test

    There are two commonly reported estimates of effect size for the independent samples t-test, including eta squared (η2) and Cohen’s d . Eta squared is analogous to r2. It estimates the amount of variance in Y that is attributable to group differences in X. Eta squared ranges from 0 to 1.0, and it is interpreted similarly to r2 in terms of “small,” “medium,” and “large” effect sizes. Eta squared is calculated as a function of an obtained t value and the study degrees of freedom.

    Cohen’s d is an alternate effect size representing the number of standard deviations the two population means are in the sample. A small Cohen’s d (< .20) indicates a high degree of overlap in population means. A large Cohen’s d (> .80) indicates a low degree of overlap in population means.

    Testing Assumptions: The Shapiro-Wilk Test and the Levene Test

    Recall that two assumptions of the t-test are that:

    4. Outcome variable Y is normally distributed.

    5. The variance of Y scores is approximately equal across groups (homogeneity assumption).

    The Shapiro-Wilk Test

    In addition to a visual inspection of histograms and skewness and kurtosis values, SPSS provides a formal statistical test of normality referred to as the Shapiro-Wilk test. A perfect normal distribution will have a Shapiro-Wilk value of 1.0. Values less than 1.0 indicate an increasing departure from a perfect normal shape. The null hypothesis of the Shapiro-Wilk test is that the distribution is normal. When the Shapiro-Wilk test indicates a p value less than .05, the normality assumption is violated.

    To obtain the Shapiro-Wilk test, in SPSS select “Analyze…Descriptive Statistics…Explore.” Place the outcome variable Y in the “Dependent List” box and select the “Plots” option. Select the “Normality plots with tests” option. Press “Continue” and then “Ok.” SPSS provides the Shapiro-Wilk test output for interpretation. A significant Shapiro-Wilk test ( p < .05) suggests that the distribution is not normal and interpretations may be affected. However, the t-test is fairly robust to violations of this assumption when sample sizes are sufficiently large (that is, > 100).

    The Levene Test

    The homogeneity of variance assumption is tested with Levene test. The Levene test is automatically generated in SPSS when an independent samples t-test is conducted. The null hypothesis for the Levene test is that group variances are equal. A significant Levene test ( p < .05) indicates that the homogeneity of variance assumption is violated. In this case, report the “Equal variances not assumed” row of the t-test output. This version of the t-test uses a more conservative adjusted degrees of freedom ( df) that compensates for the homogeneity violation. The adjusted df can often result in a decimal number (for example, df = 13.4), which is commonly rounded to a whole number in reporting (for example, df = 13). If the Levene test is not significant (that is, homogeneity is assumed), report the “Equal variances assumed” row of the t-test output.

    Proper Reporting of the Independent Samples t-Test

    Reporting a t-test in proper APA style requires an understanding of the following elements, including the statistical notation for an independent samples t-test (t), the degrees of freedom, the t value, the probability value, and the effect size. To provide context, provide the means and standard deviations for each group. For example, imagine an industrial/organizational psychologist randomly assigns 9 employees to a treatment group (for example, team-bonding exercises) and 9 employees to a control group (for example, no exercises) and then subsequently measures their rates of organizational citizenship behavior (OCB) over a period of six months. The results show:

    The mean OCB scores differed significantly across groups, t(16) = -2.58, p = .02 (two-tailed). Mean OCB for the control group (M = 67.8, SD = 8.2) was about 10 OCB points lower than mean OCB for the treatment group (M = 77.9, SD = 8.1). The effect size, as indexed by η2 was .30; this is a very large effect.

    t, Degrees of Freedom, and t Value

    The statistical notation for an independent samples t-test is t, and following it is the degrees of freedom for this statistical test. The degrees of freedom for t is n1 + n2 – 2, where n1 equals the number of participants in group 1 and n2 equals the number of participants in group 2. In the example above, N = 18 (n1 = 9; n2 = 9). The t value is a ratio of the difference in group means divided by the standard error of the difference in sample means. The t value can be either positive or negative.

    Probability Value

    A researcher estimates the probability value based on a table of critical values of t for rejecting the null hypothesis. In the example above, with 16 degrees of freedom and alpha level set to .05 (two-tailed), the table indicates a critical value of +/- 2.12 to reject the null hypothesis. The obtained t value above is -2.58, which exceeds the critical value required to reject the null hypothesis. SPSS determined the exact p value to be .02. This p value is less than .05, which indicates that the null hypothesis should be rejected for the alternative hypothesis (that is, the two groups are significantly different in mean OCB).

    Effect Size

    A common index of effect size for the independent samples t-test is eta squared (η2). SPSS does not provide this output for the independent samples t-test, but it is easily calculated by hand with the following formula: t2 ÷ (t2 + df). In the example above, the calculation is (-2.58)2 ÷ [(-2.58)2 + 16] = 6.65 ÷ (6.65 + 16) = 6.65 ÷ 22.65 = .29. This eta squared value falls between < .20 and > .80, and is therefore a “medium” effect size.

    References

    Lane, D. M. (2013). HyperStat online statistics textbook. Retrieved from http://davidmlane.com/hyperstat/index.html

    Warner, R. M. (2013). Applied statistics: From bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage Publications.

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