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AP0609-Advanced Anylytical Techniques > Statistics > Flashcards

Flashcards in Statistics Deck (20)
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1
Q

What is a t-test and why would you use it?

A

A t-test is a statistical test that is used to compare the means of two groups.

It is used to determine if populations have a significant difference or this difference is down to variance.

2
Q

What is a P value?

A

p-value from a t test is the probability that the results from your sample data occurred by chance.

3
Q

What P value should you use and why?

A

The p-value must be in the portion of the t-distribution that contains only 5% (0.05) of the probability mass.
P > 0.05 is the probability that the null hypothesis is true

4
Q

What is the T value?

A

The t-value, or t-score, is a ratio of the difference between the mean of the two sample sets and the variation that exists within the sample sets.

The greater the magnitude of T, the greater the evidence against the null hypothesis. This means there is greater evidence that there is a significant difference. The closer T is to 0, the more likely there isn’t a significant difference.

T critical at 0.05 p is 1.895. so, we accept T values above this.

5
Q

You complete a T test comparing two variables your T value is 0.75, what does this mean and why?

A

This T value is below T critical of 1.895 so this means that there is no signifcant difference between the groups, this is because the T critical at 0.05p is 1.895 so anything below this would mean the Nul hypothesis likelihood is more than 5%.

6
Q

How do you calculate degrees of freedom.

A

df = N₁ + N₂ - 2 N=sample number

7
Q

What is degrees of freedom

A

degrees of freedom is the number of values in the final calculation which are free to vary.

Df = n- 2

8
Q

What is a paired t test?

A

The paired t test compares means from the same sample group before and after a specific intervention, or period of time.

9
Q

What is a chi squared test?

A

A chi-square test is a statistical test used to compare observed results with expected results of Association.

The purpose of this test is to determine if a difference between observed data and expected data is due to chance, or if it is due to a relationship between the variables you are studying.

10
Q

Why should you do a two-tailed test?

A

Do not state the direction you are testing e.g 1 tail would be testing for a positive test or negative not and.

11
Q

What is beta in power calculations.

A

beta is the significance level, and is the probability of a type II error (a false negative)

12
Q

What is alpha in power calculations.

A

alpha is the significance level, and is the probability of a type I error (a false positive)

Alpha is the probability of a false positive which is 5%

13
Q

When would you use Anova?

A

ANOVA is used when comparing continuous, quantitative data for more than 2 groups.

14
Q

What is an F value?

A

The F-value in an ANOVA is calculated as: variation between sample means / variation within the samples.

The higher the F-value in an ANOVA, the higher the variation between sample means relative to the variation within the samples.

The higher the F-value, the lower the corresponding p-value.

15
Q

What is effect size definition and how would you calculate this?

A

The measure of the strength of a relationship between two variables.
This can be calculated by doing
Mean 1- mean 2
/
SD
Effect size
low - 0.2
medium - 0.5
high - 0.8

The effect size (ES) measures the strength of the result
It is solely magnitude-based; it does not depend on sample size

16
Q

Explain a type 1 error.

A

Type I error rate (α) is set to 0.05 and is the chance of a false positive which is the possibility that the nul hypothesis is actually correct.

17
Q

What is the power calculation and what does this tell you.

A

Power = 1-Beta

Probability of correctly rejecting the nul hypothesis

beta - probability of incorrectly retaining a null hypothesis - Type 2

18
Q

Why do we do a statistical analysis?

A

Emphasise that your study has sufficient power to find differences based on a p-value

19
Q

What does a A priori power calculation measure and why would you use this.

A

A priori power analysis done in planning phase to determine N, study size Necessary to justify project resources in funding processesMinimise use of animals or risk to patients in clinical research

20
Q

What does a Post-hoc power calculation measure and why would you use this.

A

Post-hoc power analysis done on completion of study to determine Observed PowerNecessary to check that your expected and measured ES align well
Not recommended as it makes an assumption that your results are incorrect.