WEEK 11: Inferential Statistics

Question 1

What are descriptive statistics?

Answer 1

Measures of central tendency
Measures of dispersion

Question 2

Limitations of descriptive statistics
What does descriptive data do? (summarises the data collected from?)
Can it be generalized to the wider population?
What do we use to make the data generalizable to others?

Answer 2

Descriptive statistics summarise the data collected from the SAMPLE
It cant be generalised to other people
In order to make the data generalisable to other people we have to use inferential statistics

Question 3

Inferential statistics
The aim? (to make… about?)
What does a sample have to be in order for a researcher to make inferences from the gathered data?

Answer 3

Aim: Infer from the sample data what happens in the population
Make inferences about the population on the basis of the sample (which is representative of the population

Question 4

Standard normal distribution
M =? What does it stand for?
SD =? What does it stand for?
What do the collected scores have to be transformed into so that they can be used?

Answer 4

M (mean) = 0
SD (standard deviation) = 1

In order to use the collected scores, the scores need to be transformed into z-scores

Question 5

Z-Scores
What type of score is it? What distance does it indicate?
What does a positive z-score mean?
What does a negative z-score mean?

Answer 5

Z-scores are standardised scores that indicate the distance of the scores from the mean

A positive z-score = score is above the mean
A negative z-score = score is below the mean

Question 6

Z-score calculation
What does it assume about the distribustion of data?

Answer 6

Assume that the data is normally distributed
Standardised- M =0 SD = 1
A z-score = the actual score - the mean / standard deviation (z= x- x / s)

Question 7

Z-score calculation
What does it assume about the distribution of data?
M =? SD =? ss?
Calculation for Z-score

Answer 7

Assume that the data is normally distributed
Standardised- M =0 SD = 1
A z-score = the actual score - the mean / standard deviation (z= x- x / s)

Question 8

What do z-scores allow us to compare?

Answer 8

Compare two scores from two different samples

Calculate z-scores to compare results against a set mean to determine which one did better

Question 9

What is ‘mean of the sampling distribution’?

Answer 9

The mean of all the sample means

Question 10

Standard error (SE)

Answer 10

Estimate standard error on the basis of the sample size and the standard deviation

Definition: a measure of the degree to which each sample mean deviates from the mean of the sample means
The standard deviation of the sampling distribution of the mean
The standard error of the mean indicates how accurate the estimate of the sample mean is of the population mean

Question 11

Large vs small standard error

Answer 11

Small standard error = sample mean more accurate estimate of the population mean mean

Large standard error = More variability = sample men is a less accurate estimate of population mean

Question 12

Calculating standard error
Equation?
What two things are needed?

Answer 12

SE = S/ square root of N
To calculate standard error = sample size (s) and standard deviation (n)