FAILED EXAM

1. For one sample t-test, please examine the mean of one quantitative variable and compare it with a hypothsized population mean that you think reasonable. Copy the one quantitative variable in a separate spreadsheet and do the test procedures following the publisher's video #52 shows you or you can calculate using hand or excel following the course PPT.  If you use P value method, be sure to examine the decimals of p value and check it again your significant level.   A number like 2.01E-27 is less than 0.0001.

2. For two sample t-test, please examine the mean of one quantitative variable against a categorical variable with two, only two groups. You need to copy the one quantitative variable and the one categorical variable in a separate spreadsheet, and then do the test procedures following the publisher's video #58 of F-test for variance first and then video #54 two sample t-test assuming equal variance or #56 two sample t-test assuming unequal variance, based on the result of #58's variance test. If p value of #58 is less than significant level, use video #56, otherwise video #54. Question 2 asks for comparing only female and male, be sure to only those rows for female and male and copy the quantitative variable value into two columns, one for female and one for male before you perform the video procedures.

3. For  ANOVA one -factor test, please examine the mean of one quantitative variable against a categorical variable with two or more groups. You need to copy the one quantitative variable and the one categorical variable in a separate spreadsheet, organize the quantitative variables into separate columns according to the number/name of the categroies, and then do the test procedures. For ANOVA one factor analysis, following the publisher's video #59.

4. For Chi-square test, please examine two variables using crosstabulation to see whether the two variables are indepdent from each other as video #67 shows or one variable as video #66 shows. I am fine with either way of testing. 

5. For regression analysis, please examine one dependent quantitative variable against one or more independent variables. For independent variables, only quantiatie variables and dummy variables (value = 0 or 1) can be included. Categorical variables should be not directly included in independent variables. The depdent variable must be something that could be changed by other things. For example, you cannot change your age because of change in other things. Thus, age should not be a dependent variable, but your salary can be dependent variable. If it is one independent variable, please follow video #63. If it has more than one independent variable, please follow video #65.