Solution-Explore the relationship between several variables

Explore the relationship between several variables

Reference no: EM132043719

Locate the data set "Census.sav" and open it with SPSS.

Follow the steps in section 7.14 Learning Activity as written.

Answer questions 1-3 in the activity based on your observations of the SPSS output.Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.

Locate the data set "SPSS_CUST.sav" and open it with SPSS. Follow the steps in section 8.10 Learning Activity as written. Answer all of the questions in the activity based on your observations of the SPSS output.

Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor.

The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment. Locate the data set "Census.sav" and open it with SPSS. Follow the steps in section 9.20 Learning Activity as written.

Answer questions 1-3 in the activity based on your observations of the SPSS output. Type your answers into a Word document.

Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor.

The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.

The overall goal is to run the Independent-Samples T Test, to interpret the output and visualize the results with an error bar chart.

1. We want to see whether men and women differ in their mean socioeconomic index (sei) and their age when their first child was was born (agekdbrn). First, use the Explore procedure to view the distributions of these two variables by gender. Are they similar or different? Do you see any problems with doing a t test?

2. Now do a t test for each variable, by gender. Is the homogeneity of variance assumption met, or not? What do you conclude about mean differences by gender?

3. Create an error bar chart for each variable by gender. Is the graph consistent with the result from the t test?

4. Now do the same analysis with the variable race, testing whether there are differences in sei and agekdbrn comparing whites to blacks. Although race has three categories, you can use only two categories in the t test. As before, first use the Explore procedure to view the distributions of these two variables by race? Are they similar or different? Do you see any problems with doing a t test?

5. Now do a t test for each variable, by white versus black. Is the homogeneity of variance assumption met, or not? What do you conclude about mean differences between whites and blacks?

6. Create an error bar chart for each variable by race. Is the graph consistent with the result from the t test?

7. For those with more timed: How could you display an error bar chart with only the categories of white and black, not other? There are at least two methods.Locate the data set "Census.sav" and open it with SPSS.

Follow the steps in section 7.14 Learning Activity as written.

Locate the data set "Census.sav" and open it with SPSS. Follow the steps in section 7.14 Learning Activity as written. Answer questions 1-3 in the activity based on your observations of the SPSS output.Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.

8.10 Learning Activity The overall goal of this learning activity is to use the Paired-Samples T Test.

1. One variable in the customer survey asked about agreement that SPSS products are a good value (gdvalue). A second question asked about agreement that SPSS offers high quality products (hiqualty). Use a paired-samples t test to see whether the means of these two questions differ (they are measured on a five-point scale). What do you conclude?

2. Then test whether there is a mean difference between agreement that SPSS products are easy to learn (easylrn) and SPSS products are easy to use (easyuse). What do you conclude?

3. Could we use a paired-sample t test to compare how long a customer has used SPSS products (usespss) and how frequently they use SPSS (freqspss)? Why or why not?

The SPSS customer satisfaction data file SPSS_CUST.SAV.

This data file was collected from a random sample of SPSS customers asking about their satisfaction with the software, service, and other features, and some background information on the customer and their company.

2. Then test whether there is a mean difference between agreement that SPSS products are easy to learn (easylrn) and SPSS products are easy to use (easyuse). What do you conclude?

3. Could we use a paired-sample t test to compare how long a customer has used SPSS products (usespss) and how frequently they use SPSS (freqspss)? Why or why not?Locate the data set "SPSS_CUST.sav" and open it with SPSS. Follow the steps in section

8.10 Learning Activity as written. Answer all of the questions in the activity based on your observations of the SPSS output. Type your answers into a Word document. Copy and paste the full SPSS output including any supporting graphs and tables directly from SPSS into the Word document for submission to the instructor. The SPSS output must be submitted with the problem set answers in order to receive full credit for the assignment.

9.20 Learning Activity The overall goal of this learning activity is to use One-Way ANOVA with post hoc tests to explore the relationship between several variables.

You will use the PASW Statistics data file Census.sav.

1. Investigate how the number of siblings (sibs) varies by highest degree (degree). Ask for appropriate statistics.

2. Is the assumption of homogeneity of variance met? Is the ANOVA test significant at the .01 level?

3. Do a post hoc analysis, if justified. Ask for both the Bonferroni and Scheffe tests? What do you conclude from these tests? Which education groups have different mean numbers of children? Are the Bonferroni and Scheffe tests consistent?

4. Create an error bar chart to display the mean differences for sibs by degree. Is the error bar chart a correct representation of which means are different?

5. Now do another analysis of political position (polviews) by degree. Repeat the same steps from the analysis above. Which education groups differ in their political position?

The file Census.sav, a PASW Statistics data file from a survey done on the general adult population. Questions were included about various attitudes and demographic characteristics?

1. Investigate how the number of siblings (sibs) varies by highest degree (degree). Ask for appropriate statistics.

2. Is the assumption of homogeneity of variance met? Is the ANOVA test significant at the .01 level?

4. Create an error bar chart to display the mean differences for sibs by degree. Is the error bar chart a correct representation of which means are different?

5. Now do another analysis of political position (polviews) by degree. Repeat the same steps from the analysis above. Which education groups differ in their political position?

The file Census.sav, a PASW Statistics data file from a survey done on the general adult population. Questions were included about various attitudes and demographic characteristics. Supporting Materials