From the General Social Survey dataset found in this week’s Learning Resources, use the SPSS software and choose one continuous and one categorical variable Note: this dataset will be different from your Assignment dataset). As you review, consider the implications for positive social change based on the results of your data. By Day 3 Post, present, and report a descriptive analysis for your variables, specifically noting the following: For your continuous variable: Report the mean, median, and mode. What might be the better measure for central tendency? (i.e., mean, median, or mode) and why?   Report the standard deviation. How variable are the data? How would you describe this data? What sort of research question would this variable help answer that might inform social change? Post the following information for your categorical variable: A frequency distribution. An appropriate measure of variation. How variable are the data? How would you describe this data? What sort of research question would this variable help answer that might inform social change? Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.

What is it meant by the term “parameter of a population”? Explain why a population can be represented by a random variable.What is a point estimate, and an unbiased point estimate? Explain how the sample mean can be an unbiased estimate of the population mean. How do you justify that the sample variance is an unbiased estimate of the population variance? What is the sampling requirement in the latter case? Provide a numerical example of estimating the mean, the variance, and the standard deviation.Please define each of the following terms, discuss applicability and significance of each: sample statistic, standard error, sampling distribution, and central limit theorem. Include hypothetical examples for better clarity. What is the z statistic and what qualifies a statistic to be z statistic based on the central limit theorem and the basic properties of normal distributions? What are the limitations of the central limit theorem, and how some of these limitations are bypassed? For example, the z statistic as the sampling distribution in estimating a proportion.What is the sampling distribution in estimating the variance of a population? What are the properties of this distribution?What is the alternative of z statistic for normally distributed populations which eliminates some limitations of the central limit theorem? How this sampling distribution is constructed as a combination of a z distribution and a chi squared distribution? What are the properties of this distribution? (To provide numerical examples to answer questions mentioned above, for example, in the third item above, you can use the Excel function RAND to generate a sample of a uniform random variable, and the combination of RAND and NORM.INV to generate a sample of a normal random ).Please use APA format with peer reviewed references .