prepare a quantitative data set using online sources for data analysis.

prepare a quantitative data set using online sources for data analysis. Your dataset should contain at least 50 observations and at least 5 variables (at least two variables with interval-level measurement and at least one variable with categorical measurement). You should use descriptive statistics (mean, median, standard deviation, minimum, and maximum) to summarize interval variables and frequency distribution to summarize categorical variables. You are also required to use two inferential analysis techniques one of which must be multivariate linear regression and the other technique you choose 2 yourself from those learned in class to test meaningful research hypotheses. The dependent variable in a regression model should be measured at the interval level. You are expected to answer the following questions in your essay: 1) What are your research question and hypotheses? Please make sure that (a) your research question is from public (nonprofit) administration field, (b) each of your hypotheses proposes an impact of one independent variable on a dependent variable, and (c) each of your hypothesis sounds reasonable. 2) Describe the dataset you are using: What are your observations and how many observations are in the sample? Where did you get the data? (Please provide the online link) When and who collected the data? 3) How is each of the variables in your hypotheses measured? What is the measurement unit for the variable(s) measured at the interval level? If you recoded variables or generated new variables, please explain how you did that. 4) Use basic descriptive statistics to summarize at least two interval variables and use frequency distribution to summarize one categorical variable. 5) Which techniques do you use to test your hypotheses? Why do you think these techniques are appropriate? Please make sure you specify your dependent variable and independent variables in your inferential analyses. 6) Interpret the analysis results and report whether each of your hypotheses is supported or not. In correlation analysis, please (a) interpret the correlation coefficient and then (b) use the t test result to show the significance of the relationship. If you apply contingency table with chi square test, please (a) use the column percent to report the specific relationship, and (b) use chi square test to show whether the relationship is significant. If you use group mean comparison with t test, please (a) compare the sample means first, and then (b) use t test result to report whether the difference is significant or not. 7) When you interpret the results of the multivariate linear regression, please (a) explain each of the partial coefficient, (b) the significance of the partial coefficients, and (c) also report the model fit statistics. Please submit your essay (in MS Word) as well as data file (in Excel)

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