week 6 SCM (t-tests)

Question 1

what is the difference between descriptive statistics and inferential statistics?

Answer 1

• descriptive statistics is basic features of data such as mean, median, spread
• Inferential statistics attempts to draw generalised conclusions beyond the data

Question 2

what does quantitative statistics do?

Answer 2

• allows us to relate properties of an appropriate sample to the population of which the sample was taken

Question 3

what is the difference between a dependent and independent t-test?

Answer 3

• independent t-test is for two different/independent groups

- dependent t-test is for related data. For example matched samples or the same sample at different points in time

Question 4

what would we expect from the means if they come from the same population?

Answer 4

• if the same means come from the same population we would we would expect them to be roughly equal
• if the means come from different populations we would expect them to be more different

Question 5

how can we tell if two sample means are likely to be from different populations?

Answer 5

• if the difference between the two means is larger than we would expect based on the SEM they are likely to be from different populations

Question 6

what is an alternative explanation for the difference between the two means being larger than we would expect based on the SEM?

Answer 6

• the two sample means could be from the same population but happen to both be atypical to the parent population. This is very unlikely

Question 7

what can we assume as the difference between the two sample means get larger?

Answer 7

• the more confident we become that the observed difference is due to experimental manipulation and not by chance

Question 8

what is the T Test fomula?

Answer 8

T= (observed difference between sample means - expected difference between population means) / estimate of the standard error of the difference between two sample means

Question 9

what is the general idea of the General linear model?

Answer 9

The model for the dependent variable is composed of a linear combination of independent variables, each one multiplied by weight(b)