Modules Week 1

Question 1

What are the 3 types of quantitative psychological research?

Answer 1

1. Difference – is one group of people different to another in some way? MBB2 online modules focus on this.
2. Association – is one construct related to another? A MBB2 tutorial class will address this
3. Prediction – does one construct influence another? You will learn about this in future psychology subjects

Question 2

What is the goal of psychological research?

Answer 2

When we conduct a psychological research project, our aim is to make inferences (in other words, suggestions or claims) about a population. Put simply, we want to say something about a population.

Question 3

What is a population?

Answer 3

• A population is everyone of interest to a research question. In other words, it is the research question that defines the population.
• For example, a study may investigate wellbeing in university students. In this case, the corresponding population would be all people who are university students.

Question 4

What are mean scores indicators of?

Answer 4

In quantitative terms, mean scores will be our indicator of what is typical. We know the population mean in this example. We could compare our sample mean to this value to assess evidence for a difference.
Based on the results of this comparison, we will make an inference about the population of psychology students and whether or not it is likely to differ from the general population in intelligence.

Question 5

Summarise inference

Answer 5

• Quantitative psychological research aims to generate knowledge about populations.
• A population is everyone of interest to a research question.
• Because we usually can’t measure a population in its entirety, a sample is drawn from the population and measured.
• We can make inferences about the population based on the evidence observed in the sample.
• In these MBB2 modules, we will focus on inference about differences in means scores.

Question 6

Describe distributions of data

Answer 6

When measured, constructs takes on different values for different people in a sample.

Collectively, those different values form a distribution of data, which can be described in terms of central tendency and variability.

Question 7

What are mean and standard deviation measuring in this subject?

Answer 7

Mean = measure of central tendency

Standard Deviation = measure of variability

Question 8

What is a normal shape?

Answer 8

Most of the people are in the middle. The peak of the graph.

Relatively fewer people are on the outsides. The tails of the graph.

Question 9

What is the 2s rule of thumb?

Answer 9

In a distribution with a normal shape, 95% of scores fall within approximately 2 standard deviations (s) of the mean.

We can think of those scores inside 2 standard deviations (s) of the mean as being typical. They are expected as they occur frequently in this distribution.

We can think of those scores outside 2 standard deviations (s) of the mean as being extreme. They are not expected as they occur infrequently in this distribution.

Question 10

How is the 2s rule of thumb applied?

Answer 10

Double Standard deviation, then add and subtract it from the mean to get critical limits for determining what is typical or extreme

To apply our rule of thumb:
m = 46.87
s = 4.84 × 2 = 9.68

Lower limit
46.87 - 9.68 = 37.19

Upper limit
46.87 + 9.68 = 56.55

Question 11

What is a z score?

Answer 11

A z-score, also known as a standard score, measures how many standard deviations a data point is from the mean of a dataset

Question 12

How can we convernt a raw score to z score?

Answer 12

We can also convert raw scores into z scores to get a better idea of where in the distribution those scores fall. Let’s say we get a score of 68 on an exam. We may be disappointed to have scored so low, but perhaps it was just a very hard exam. Having information about the distribution of all scores in the class would be helpful to put some perspective on ours. We find out that the class got an average score of 54 with a standard deviation of 8. To find out our relative location within this distribution, we simply convert our test score into a z score.
z= X−μ/σ = 68−54/8 =1.75

Question 13

What is the formula for converting a z score to x score for a population?

Answer 13

x=zσ+μ

Question 14

What is the formula for converting a z score to x score for a sample?

Answer 14

x=zs+M

Question 15

Example of turning raw scores into z scores

Answer 15

Notice that these are just simple rearrangements of the original formulas for calculating z from raw scores.

Let’s say we create a new measure of intelligence, and initial calibration finds that our scores have a mean of 40 and standard deviation of 7. Three people who have scores of 52, 43, and 34 want to know how well they did on the measure. We can convert their raw scores into z scores:
z = 52-40/7 = 1.71, z = 43-40/7 = 0.43, z = 34-40/7 = -0.80