pls help, all answers are incorrect :(

1 point 16. Suppose the researcher tested whether the average scale score for procrastination was the same for students who did and did not graduate, and the test statistic was not significant. The null hypothesis was therefore not rejected. Later, it turned out that there was conclusively an effect after all different population averages of both groups). What can we conclude? The researcher initially Made a Type i error Made a Typell error Drew correct conclusions 1 point 22. All the students begin their courses with an introductory course. The researcher wonders if the proportion of students who passed the introductory course is equal to the proportion who graduated. The table below shows the proportions. Not graduated Graduated Total Not passed introductory 97 81 178 Passed introductory 64 158 222 Total 161 239 400 What is the p-value associated with the test statistic for two-sided test? 1.4118 1 point 23. Course duration was predicted through a multiple regression test using procrastination, 10. gender, achievement motivation and failure anxiety. See sum of squares output below. Sum of Squares Mean Square P Regression 8275,689 5 1655.138 4618 0.001 Residual 50173.825 140 358 384 Total 58449.514 145 What is the multiple correlation value? 0.1416 point 28. To test whether or not passing the first year depends on the student's procrastination score, a logistic regression analysis was conducted. The test also controlled for gender (female = 0. male = 1). See the results in the table below. SE d Sie Exp!B) Procrastination 0.397 0.192 0.039 1.487 Gender 0.672 0.301 1 0.026 1.959 Intercept -2.472 0.583 1 0.000 0.084 Mean procrastination was 2.7479, with a standard deviation of 0.77183. Based on the logistic regression model, what is the probability that a male student who has a procrastination score one standard deviation above the mean passes the first year? 0.5993 point 29. The researcher wants to test whether mean procrastinating score (in a subset of students), is higher for those that graduated compared to those that did not graduate. Using a table, what is the upper limit of the probability threshold for the relevant test statistic (p<.. n mean standard deviation error not graduated>