Question Prompt:Factual answers How many more men than women in the sample were self employed?For which occupation is there the largest difference between men and women?What is the value of chi-square for the occupation of “Operators, fabricators, and laborers”?What is the value of p for the difference between the percentage of men who are “Operators, fabricators, and laborers” and the percentage of women who are “Operators, fabricators, and laborers”?Based on your answer to question 4, should the difference be declared to be statistically significant?Are all the differences between occupations statistically significant at the same probability level? If yes, at what level?Compare the probability level for “High school graduate” with the probability level for “Bachelor’s degree or more.” Which one is more significant? Explain.Should the null hypothesis be rejected for the difference in the percentages of men and women for “Craft, precision, production, and repair”? Why? Why not?Is the difference for “Some college” statistically significant? Explain the basis for your answer.Should the null hypothesis for “Immigrated to the United States” be rejected? Explain the basis for your answer. Colleauge Response :In this week’s assignment, we are examining data provided from a study that examined a strictly Hispanic population. The exercise looked at data collected in an effort to determine if there is a correlation in a Hispanic population of subjects who were self-employed, based on gender. When looking at the variables provided, gender is a nominal variable. There is no order to being male or female. The data for the type of occupational is also a nominal variable. Educational level is also examined. There is a sense of order or hierarchy to this, so it could be considered ordinal. When considering educational level, this could also correlate with the level of income, which was not measured in this study. Lastly, immigration status was evaluated. Were the subjects born in this country did they move here? The information is a nominal variable, but the implication is that a subject has chosen to leave their country of origin, with a desire for an advanced opportunity. To participate in the study, subjects had to be self-employed. This is another nominal variable, but information that suggests an initiative in personality was present, with a desire to be one’s, own boss. This was inherently a group of self-starters, with some desire to control their own destiny. In this exercise, we were given the statistical data by the percentage of the variable groups and also chi-square values to correlate the difference between sample groups. P-values were listed based on the chi-square values. As noted by Turhan (2020) X, chi-square testing is a good choice to evaluate this type of data, which is comprised of non-numeric variables, and the total number of variables being compared is not large. Zuh (2016) notes that statistical hypothesis testing may rely too much on the p-value with the advent of computer programs so run the statistical data. When research was done in the past, probability data was not determined until after the data collection was complete. This perhaps led to more pure hypothesis testing. The question is posed that has research taken a turn to simply finding the smallest p-value to support research hypotheses?
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