Statistics: Important concepts - hypotheses, significance and choosing the right test

Question 1

What is the variance?

Answer 1

the sum of all the squared differences divided by the number of samples we have ( - 1)

Question 2

What is the standard deviation?

Answer 2

The average difference from the mean

square root of the variance

Question 3

What is a property of the normal distribution?

Answer 3

The concept that 95% of the data lies within 2 standard deviations of the mean.

Question 4

What is the standard error or the mean?

Answer 4

A measure of the precision of the estimate

Question 5

How do you calculate standard error of the mean?

Answer 5

𝑆𝐸𝑀 = 𝑆𝐷/Root(𝑛)

Question 6

how do you calculate the 95% confidence limit of a mean?

Answer 6

𝑆𝑎𝑚𝑝𝑙𝑒 𝑚𝑒𝑎𝑛 ±(1.96 ×𝑆𝐸𝑀)

Question 7

What are confidence intervals?

Answer 7

Confidence intervals are an indication of how reliable our estimate is, given the data we have

Question 8

What are confidence levels usually set at?

Answer 8

95, 90, 99%

Question 9

What are P-values

Answer 9

P-values were devised to indicate how unlikely our result would be IF IN FACT THERE IS NO REAL EFFEC

Question 10

What is the null hypothesis?

Answer 10

A statement of equality usually formed first to state the their is potentially no difference/ no relationship between variables.

Question 11

What is the alternative hypothesis?

Answer 11

A statement of inequality stating that there is a difference between 2 variables or a difference in relationship. This can either be directional or non-directional

Question 12

What is a non-directional hypothesis?

Answer 12

reflects a difference between groups but the direction of difference is not specified (eg. increase or decrease)

Question 13

What is a directional hypothesis?

Answer 13

this reflects a difference between the groups , and the direction

Question 14

What is the significance level?

Answer 14

The level of evidence we require to prove that there is something going on and to conclude the hypothesis and to accept or reject the null hypothesis.

Question 15

What is a type 1 error?

Answer 15

When we reject the null hypothesis when it is true.

We conclude that there is an effect when there truly isn’t one.

Question 16

What is a type 2 error?

Answer 16

We do not reject the null hypothesis when it is false, by concluding that there is not enough evidence of an effect when one truly exists.

Question 17

What is the P-value

Answer 17

the probability of obtaining the result, or something more extreme, if the null hypothesis were true

(The smaller the p-value, the greater the evidence against the null hypothesis)

Question 18

What is a parametric test?

Answer 18

based on the assumption that you data follows a determined distribution

Question 19

What is a non-parametric test?

Answer 19

if you can’t assume the data follow any particular distribution, but they are less potentially less powerful