Proability and Distributions

Question 1

How do you calculate Pearson’s coefficient of skew using the median and the mean?

Answer 1

𝑆𝑘𝑒𝑤= 3(𝑀𝑒𝑎𝑛−𝑀𝑒𝑑𝑖𝑎𝑛)
÷
(𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛)

Question 2

If the data skew is <0, the data is?

Answer 2

Negatively skewed

Question 3

If the data skew is >0, the data is?

Answer 3

Positively skewed

Question 4

What do parametric tests assume?

Answer 4

assumes values such as the mean and SD accurately reflect the population distribution

Question 5

What is the equation for scores?

Answer 5

𝑍= (𝐼𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙 𝑝𝑜𝑖𝑛𝑡
−𝐺𝑟𝑜𝑢𝑝 𝑀𝑒𝑎𝑛)
÷
(𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝐷𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛)

Question 5

Pros of Z scores?

Answer 5

Can transform data to a standardised scale.

Scale adheres to normal distribution.

Use the entire dataset.

Question 6

The estimated value of a population which was based on a sample that differs from the true mean of the global population, or other samples is known as what?

Answer 6

Sampling Error

Use Standard error(SE) of the mean to say how confident we are that our sample values represent the population

Question 7

What tells us how likely it is our sample will vary from one sampling to another?

Answer 7

Standard Error (SE)

can also use confidence intervals instead

Question 8

What can influence the STANDARD Error

Answer 8

Variability of the original data (refers to the SD of the population)

Total N used to create the sample mean

Question 8

What is the range of values that, in a certain proportion of samples (e.g. 95%), contain the true value of a statistic (e.g. the mean)?

Answer 8

Confidence intervals

Question 9

Give an example of what Confidence intervals be used for:

Answer 9

Can be used for visualisation (Error Bars)

Non-overlapping SEM bars often imply significant differences between conditions (bar graph)

Question 9

How are Z scores useful?

Answer 9

They reduce skew
Compare individual data to the mean

Question 10

Sampling errors are accounted for by calculating what?

Answer 10

The SE of the mean
or the Confidence intervals