1st scenario.

1. A school psychologist administers an interview assessment that screens for possible post-traumatic stress disorder (PTSD) to school children who live in an area that was recently affected by a natural disaster. She assumes that children in this area have higher scores than children in the general population, who normally score a 2.3. The following table shows the scores for a particular class of children at the school. Using the table, enter the data into a new SPSS file and conduct a single sample t-test to evaluate whether or not these children scored higher than the general population.
   
2. Write a sentence that includes the t and p values, and a statement about the test’s significance, as it might appear in a Results section.
3. A math teacher wants to evaluate whether or not a new method of teaching leads to improved scores on a geometry test. To test this claim she administers similar geometry tests to 16 students before and after they have been introduced to the new method. Using the table below, enter the data into a new SPSS data file and test the math teacher’s claim using a t-test for dependent means (paired t-test).
   
   
4. The null hypothesis for this scenario can be written as follows: "There is no difference between mean test scores before and after the introduction of the geometry teaching method (M before = M after)." should this hypothesis be accepted or rejected, and why? Write your answer in sentence form.

2nd scenario.

Peter was interested in determining if children who hit a bobo doll more frequently would

display more or less aggressive behavior on the playground. He was given permission to observe 10 boys in a nursery school classroom. Each boy was encouraged to hit a bobo doll for 5 minutes. The number of times each boy struck the bobo doll was recorded (bobo). Next, Peter observed the boys on the playground for an hour and recorded the number of times each boy struck a classmate (peer).

1. Conduct a linear regression to predict the number of times a boy would strike a

classmate from the number of times the boy hit a bobo doll. From the output, identify the following:

1. Slope associated with the predictor
2. Additive constant for the regression equation
3. Mean number of times they struck a classmate
4. Correlation between the number of times they hit the bobo doll and the number of times they struck a classmate
5. Standard error of estimate

2. What is the relationship between the multiple R and the bivariate correlation between the predictor and the criterion?

3. Create a scatterplot of the relationship between the two variables. Plot the regression line on the graph. What can you tell from this graph about the predictability of the dependent variable?

4. Write a Results section based on your analyses.

1(a). A community psychologist is interested in whether spending time in after-school programs is predictive of the number of arrests as a young adult in a high-risk neighborhood. After collecting records on 17 individuals over 8 years, the psychologist compiles the information listed in the table below. Conduct a linear regression to analyze the research question.

The steps will be the same as the ones you have been practicing in Part One of the assignment—the only difference is that you are now responsible for creating the data file as well. Remember to name and define your variables under the "Variable View," then return to the "Data View" to enter the data.

1. Construct a scatterplot of the relationship between the two variables. Plot the regression line on this graph.
2. Write the equation of the regression line using the unstandardized coefficients from your output.
3. Is time spent in after school programs predictive of the number of arrests as a young adult? Why or why not?

Lilly collects data on a sample of 130 high school students to evaluate whether the proportion of female high school students who take advanced math courses in high school varies depending upon whether they have been raised primarily by their father or by both their mother and their father. The SPSS data file contains two variables: math (0 no advanced math and 1 some advanced math) and parent (1 primarily father and 2 father and mother).

1. Conduct a crosstabs analysis to examine whether the proportion of female high school students who take advanced math courses is different for different levels of the parent variable. From the output, identify the following:

1. Percent of female students who took some advanced math classes
2. Percent of female students who took no advanced math classes when female
   students were raised by their fathers
3. Percent of female students raised by their father only
4. χ2 value
5. Strength of relationship between taking advanced math classes and level of parenting(This question is asking specifically about effect size).

2. Create a clustered bar graph to show differences in the number of female students taking some advanced math classes for the different categories of parenting.

4. Write a Results section based on your analysis. 2 to 3 sentences in length.

Part Two:

1. An industrial/organizational psychologist is helping a company determine the type of work stations preferred by its employees. The business owner believes that people who work in different departments may prefer different work station layouts. In order to examine this claim, the I/O psychologist sets up three simulated work stations: private office (PO), semi-private office (SPO), and open floor plan (OFP). She recruits employees from 3 different departments: Information Technology, Human Resources, and Marketing. The participants spend 30 minutes in each simulated work station performing general pre-arranged tasks. At the end of the 1.5 hours, the participants turn in a form on which they mark which work station they prefer. The results are listed below. Perform a chi square test of independence (using an SPSS two-way contingency table analysis) to determine whether the proportions of work station preferences differ across departments. Use the weighted cases method.
   
2. Create a clustered bar graph depicting your results.
3. Write a significance statement for your results as it would appear in an APA Results section.

3rd. scenario. Nonparametric Tests.

Billie wishes to test the hypothesis that overweight individuals tend to eat faster than normal weight individuals. To test this hypothesis, she has two assistants sit in McDonald’s restaurant and identify individuals who order at lunch time the Big Mac special (Big Mac, large fries, and large coke). The Big Mackers, as the assistants affectionately called them, were classified by the assistants as overweight, normal weight, or neither overweight nor normal weight. The assistants identify 10 overweight Big Mackers and 30 normal weight Big Mackers. (Individuals who were neither overweight nor normal weight were disregarded.) The assistants record the amount of time it took for the individuals in the two groups to complete their Big Mac special meals. One variable is weight with two levels, overweight ( 1) and normal weight ( 2). The second variable is time in seconds.

1. Compute a Mann-Whitney U test on these data. From the output, identify the

following:

1. p value
2. z value corrected for ties
3. Mean rank for normal weight individuals

3. Write a Results section based on your analyses. What should you conclude?

4. Create a boxplot.

Marvin is interested in whether blonds, brunets, and redheads differ in their extroversion. Herandomly samples 18 men from his local college campus: six blonds, six brunets, and six red-heads. He then administers a measure of social extroversion to each individual.

1. Conduct a Kruskal-Wallis test to investigate the relationship between hair color
   and social extroversion. Should you conduct follow-up tests?
2. Compute an effect size for the overall effect of hair color on extroversion. Effect size must be computed by hand (or calc)

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