USING SPSS and the data attached below, ANSWER THE FOLLOWING QUESTION.

Questions 1-2

Download the attached gss.sav (data from general social survey). Using SPSS to conduct t-tests to answer the following questions:

- Do internet users on average spend 4.5 hours per week on e-mail (variable: emailhrs)?

a. List the null hypothesis and the alternative hypothesis.

b. Use SPSS to run a one-sample t-test and include your SPSS outputs with your answer.

c. What are the t statistics and p-value of the t-test respectively, according to (b)?

d. Draw your conclusion on whether or not the null hypothesis in (a) should be rejected (use a 95% significance level), based on (c).

2. Do females and males (variable name: sex) on average spend same hours on e-mail (variable name: emailhrs)?

- List the null hypothesis and alternative hypothesis.
- To test the hypothesis, should you use an independent-sample t-test or a paired-sample t-test?
- Use SPSS to conduct the test and include your SPSS outputs with your answer.
- What are the t statistics and p-value of the t-test respectively, according to (c)?
- Draw your conclusion on whether or not the null hypothesis should be rejected, based on the t-test result.

Question 3.

Using the attached dataset World_updated.sav. Two of the variables in this file (rgdp86 and rgdp88) measure real Gross Domestic Product (GDP) per capita in 1986 and 1988 respectively. Please conduct the appropriate t-test to answer the following question: “Is there statistically significant evidence that per capita GDP in 1988 is different from that of 1986?

Please show your results and reasoning to justify your answer by answering the following questions..

- List the null hypothesis and alternative hypothesis.
- To test the hypothesis, should you use an independent-sample t-test or paired-sample t-test?
- Show your SPSS outputs.

d. What are the t statistics and p-value of the t-test respectively, according to (b)?

- Draw your conclusion on whether or not the null hypothesis in (a) should be rejected (use a 95% significance level), based on the t-test result.

Question 4.

It is believed that, the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Excel output from regressing starting salary on number of hours spent studying per day for a sample of 51 students.

Note: The format of the regression results has been purposely changed to be different from SPSS outputs; some of the numbers in the output are purposely erased

USING THE TABLE IN THE DOCUMENT .

11) Referring to the table, the estimated average change in salary (in thousands of dollars) as a result of spending an extra hour per day studying is

A) -1.8940

B) 0.7845

C) 0.9795

D) 335.04733

12) Referring to the table, the value of the measured t-test statistic to test whether average SALARY depends linearly on HOURS is

A) -4.7134

B) -1.8940

C) 0.9795

D) 13.3561

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