Inferential Statistics

Question 1

What is the purpose of descriptive statistics?

Answer 1

Helps us summarise data and help us see the key properties of features of the data, e.g. mean, mode, median (measures of central tendency), range, standard deviation (measures of dispersion)

Question 2

What is the purpose of inferential statistics?

Answer 2

• Gives us an objective way of deciding if a difference or correlation is important
• Also, they allow us to decide if the result is due to chance or reflects a genuine difference/correlation
• Allow you to reject or accept the null/alternate hypothesis

Question 3

How is probability noted:

Answer 3

P = Probability is equal
P ≤ Probability is less than or equal to
P > Probability is greater than

Question 4

In psychology, what does the P-value demonstrate?

Answer 4

Probability that the difference/correlation came out by chance

Question 5

What does P=0.05 mean?

Answer 5

Probability that the difference/correlation is due to chance is 5%

Question 6

Levels of significance are written using P values. They represent how likely it is that the results took place due to chance. P ≤ 0.05 means that:

Answer 6

the probability that the difference/correlation is due to chance is equal to or less than 5%

Question 7

Which is better P ≤ 0.01 or P ≤ 0.05?

Answer 7

P ≤ 0.01 is better as it sets a much stricter limit on what is accepted as chance compared to P ≤ 0.05

Question 8

Which P value do psychologists generally use?

Answer 8

P≤ 0.05

Question 9

What do we do with our hypothesis if P ≤ 0.05?

Answer 9

The difference/correlation is significant - we do not think it came out by chance, therefore we REJECT the NULL and ACCEPT the ALTERNATE

Question 10

What do we do with our hypothesis if P > 0.05?

Answer 10

The difference/correlation is NOT significant - REJECT the ALTERNATE and ACCEPT the NULL because results happened by chance

Question 11

What are the different levels of data?

Answer 11

• Nominal
• Ordinal
• Interval/ Ratio data

Question 12

What is the shallowest form of data?

Answer 12

nominal

Question 13

Nominal data:

Answer 13

• CATAGORICAL DATA
• data in the form of categories - discrete data
• measuring the frequency of each category
• e.g. eye colour, height, hair colour
• limited, superficial, doesn’t show data within the categories

Question 14

Ordinal data:

Answer 14

• RANKED DATA
• continous data that is ranked in positions
• cannot see difference between ranks, only order of exact differences
• made up by researcher for the study
• non-standardised
• measuring non-objective quantities
• not real world quantities

Question 15

Interval/ Ratio Data:

Answer 15

• fixed intervals on the scale, e.g. cm, ms, kg
• standardised units
• uses real world quantities
• measures objective quantities