PSY230 INTRO TO STATISTICS

Question 32 If we measure the variability of a back pain score, what variability statistic is the easiest to understand and used most often in publications? 0 range 0 sum of squares 0 standard deviation 0 variance Question 33 Sum of squares is short for O the area under a parabola 0 sum of squared distances from the mean 0 the area of a perfect square 0 the angle of attack and reection Question 34 2 pts If a group is measured prior to treatment and then after treatment and has the same mean outcome, what might you NOT inspect next to gain more insight into treatment effects? 0 did the some get better and some worse, overall kept the same mean? 0 did the distribution shape change? 0 did the post-treatment variance increase? 0 the treatment was ineffective Question 35 2 pts What statistical test would you have used for testing for clinical change between pre and post measurement? (7 Pearson's correlation coefcient, r (7 independent t-test (7 dependent t-test (T Fisher's homogeneity test D Question 36 2 pts What is the difference between a histogram and a bar chart? O a histogram displays motional data O a bar chart displays interval data a bar chart displays nominal data O there is no difference D Question 37 2 pts Which of the following represent the strongest correlation represented in the Pearson product- moment correlation coefficient among the choices? 1.96 O 0.5 O 0.0 O 1.0D Question 38 2 pts Which of the following represent the strongest correlation represented in the Pearson product- moment correlation coefficient among the choices? O 0.50 O -0.90 O -0.70 O 0.85 D Question 39 2 pts Of the following choices of graphs, which is the best way to display a bivariate (between 2 variables) correlation? scatterplot histogram pie chart O bar chartD Question 39 2 pts Of the following choices of graphs, which is the best way to display a bivariate (between 2 variables) correlation? scatterplot histogram O pie chart O bar chart D Question 40 2 pts The purpose of a coefficient of determination is to describe the amount of in the dependent variable contributed by the _ variable. O wiggle, giggle O shared variance, independent shared correlation, linear fate, God