Week 10 : RMA

Question 1

What is a z score?

Answer 1

A standard score

Question 2

How do you calculate the z score?

Answer 2

z = deviation of x (total number of score) - the mean score / divided by the standard deviation

Question 3

Why do you calculate the z score?

Answer 3

To covert normal datasets with standard normal distributions

Question 4

What are the requirements for a parametric test?

Answer 4

Normal distribution, interval or ratio data and homogeneity of variance

Question 5

What are the requirements for a non-parametric test?

Answer 5

nominal data, no assumptions

Question 6

What is the Chi-Squared test? goodness of fit x2

Answer 6

Used on unrelated data, used to answer questions about the proportions of a population distribution, used to compare different levels of one variable

Question 7

What is the formula for goodness of fit x^2?

Answer 7

x^2 = the sum of (f observed - f expected) divided by f expected

Question 8

What is f observed?

Answer 8

observed values in the table

Question 9

What is f expected?

Answer 9

sample size x probabilities

Question 10

What is the Test if independence TI?

Answer 10

Compares observed to expected frequencies

Question 11

What is the formula of TI?

Answer 11

f expected = fc (column total) x fr (row total) / divided by the number of total sample

Question 12

How do you calculate the degrees of freedom?

Answer 12

(number of rows-1) x (numbers of columns-1)