Module 2

Question 1

frequency

Answer 1

is the total number of times that an observation occurs in your data set

denoted by a “f” - gives us the quantity of raw scores

Question 2

frequency example: symptom severity

Answer 2

Mild, Severe, Moderate, Moderate, Mild, Mild, Moderate, Mild, Moderate, Moderate, Moderate, Mild, Severe, Moderate, Mild, Severe, Moderate Mild, Severe, Mild, Moderate, Mild, Mild, Moderate, Severe, Mild, Moderate, Mild, Moderate, Mild, Mild, Severe, Mild, Moderate, Mild, Moderate, Mild, Mild, Moderate, Mild, Severe, Mild, Mild, Moderate, Mild, Mild, Moderate, Mild, Mild, Moderate, Moderate, Severe

This is an ordinal variable. So, it is Qualitative

Qualitative variables have different frequency tables from quantitative ones

Question 3

relative frequency

Answer 3

This is a probability. Probabilities range from 0 – 1. It is the probability of finding a particular ranking, drawing from the sample at random

calculate by dividng the frequency of a given variable type and divide it by the total number of frequencies (total number of observations in a data set)

Question 4

2 types of quantitative variables

ungrouped data

Answer 4

Ungrouped tables = when the range of values that a person could score is less than 10

So for example…. Let’s say that we have a variable that tells us how late people were to class in minutes

People were late for class between 3 – 7 minutes… How many values do we have
3, 4, 5, 6, 7…. 5 total values!!

It’s ungrouped because we don’t make groups for scores because there are fewer than 10 possible options. We make an option for each sore in this case

Question 5

2 types of quantitative variables

grouped data

Answer 5

when the range of values are greater than 10
Let’s say we have the following IQ data…
129, 121, 118, 110, 113, 112, 111, 115, 115, 100, 100, 100, 100, 100, 109, 105, 103, 102, 101, 100, 108, 107, 106, 105, 104, 103, 99, 99, 98, 96, 94, 90, 99, 99, 99, 98, 97, 96, 95, 93, 95, 96, 80, 89, 88, 87, 87, 89, 70

Find your highest and lowest score.
We found 129 and 70.

How many values does this represent? 60 (I know some of you are thinking 59)

You want to have 5 – 10 groups. So how could we “chunk” these groups together.
Right, groups of 10!
Use Psychologically Pleasing group sizes.
2, 3, 5, 10

Question 6

raw scores

Answer 6

x marks individual scores

Question 7

how many categories does it take to make a normal distribution, on average?

Answer 7

4 categories or more

Question 8

qualitative vs quanitative graphs

Answer 8

quantitative - histograms (bars do touch)
qualitative - bar graphs (bars of data don’t touch)

Question 9

cumulative frequency

Answer 9

take the number of people who were at most a certain score and sums them

Question 10

are graphs and tables the same?

Answer 10

yes, they are different representations of the same data set

Question 11

how do you choose to use a graph or a table?

Answer 11

experience tells you, it’s up to you. Whatever is psychologically pleasing

Question 12

skewness

Answer 12

non-normal distribution of raw scores

positive skew - most scores group around lower scores
negative skew - most scores group around lower scores

Question 13

positive skew