statistics

 For this summer’s project we are going to use data from the General Social Survey (GSS). The GSS is a sociological survey created and regularly collected since 1972 by the National Opinion Research Center at the University of Chicago. It is funded by the National Science Foundation. The GSS collects information and keeps a historical record of the concerns, experiences, attitudes, and practices of residents of the United States. We are going to look at data collected in 2018 by the GSS. Click here to open the data in StatCrunch. You will find the variables listed below in the data file. Variable Description GSS Year The year the data was collected Age Age of respondent Sex Sex of respondent – Male, Female Race Race of respondent – Black, White, Other Marital status Are you currently – married, widowed, divorced, separated, never married Children Number of Children Highest Degree Respondent’s highest degree – Less than High School, High School, Junior College, Bachelor, Graduate R Income Respondents’ income T Income Total family income Job Satisfaction All in all, how satisfied would you say you are with your job? – Not at all satisfied, Not too satisfied, Somewhat satisfied, Very satisfied, Not applicable Hours Relax After work how many hours do you have to relax? Rich Work If rich, continue or stop working? – Continue working, Stop working, Not applicable General Happy General happiness – Not too happy, Pretty happy, Very happy 
1. Summarize the following variables using the proper summary measures and graphs. Do it separately for each variable.
 a. Number of children 
b. General Happiness 
2. Suppose a respondent is randomly selected from this group. a. What is the probability that the respondent is very satisfied with their job? b. What is the probability a respondent will say there are very happy given they are very satisfied with their job? 
3. Create a side-by-side boxplot for describing age of the respondent by their general happiness. Be sure to give a few sentences comparing the similarities and differences of ages for different happiness categories.
 4. Create a 99% confidence interval for the mean number of hours Americans spend relaxing after work. Be sure to include a statement interpreting the confidence interval result within the context. 
5. Respondents were asked if they were rich would they continue or stop working. Is there a significant difference in the proportion of males and females that answered that they would stop working? Use a significance level of 0.10. Be sure to demonstrate all 5 steps of the hypothesis testing process. Hint: Create a contingency table to determine your number of success and observations in each group. Only consider those that answered, “continue working” or “stop working 
 6. In the U.S. is happiness related to a person’s job satisfaction? Use the GSS data and a 0.01 significance level to determine this. Be sure to demonstrate all 5 steps of the hypothesis testing process. 7. If you could add a question to this survey. What would it be and why? Is the variable you are describing a categorical or a quantitative variable? 

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