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Sem 1 Year 2 > REBM > Flashcards

REBM Flashcards

1
Q

What is the null hypothesis?

A

Predicts no effect or relationship between variables (Ho)

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2
Q

What is the alternative hypothesis?

A

Predicts there is an effect or relationship between variables (Ha)
Sometimes called the study hypothesis

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3
Q

What are one tailed and two tailed tests?

A

One tailed= testing for the possibility of the relationship in one direction, disregarding the possibility of another direction
Two tailed= testing for the possibility of a relationship in either direction

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4
Q

Is it easier to achieve statistical significance in a one or two tailed test?

A

One- the p value is not split in either direction

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5
Q

What is p hacking?

A

Where lots of tests are ran on two sets of data with the view of getting a statistically significant value by luck. Considered highly unethical

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6
Q

What is the p value?

A

A statistical measurement used to determine the likelihood that an observed outcome is the product of chance
‘The probability of obtaining results as least as extreme assuming the null hypothesis is correct’

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7
Q

What does a p value of 0.05 mean?

A

5% of the time would see a result as least as extreme as the one you got if the null hypothesis was true

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8
Q

Can the p value ever be 0?

A

No- always a chance results were a coincidence

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9
Q

What is a type 1 error?

A

Wrongly rejecting the null hypothesis when it is true

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10
Q

What is a type 2 error?

A

Wrongly failing to reject the null hypothesis when it is false

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11
Q

Can you accept the null hypothesis?

A

NO

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12
Q

What is statistical significance denoted by?

A

Alpha

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13
Q

What is statistical significance?

A

The probability of incorrectly rejecting the null hypothesis when it is true
(the probability of making a type 1 error)

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14
Q

What is statistical power denoted as?

A

1- beta

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15
Q

What are type 1 and type 2 errors denoted by?

A

Type 1= alpha
Type 2= beta

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16
Q

What is statistical power?

A

The probability of rejecting the null hypothesis correctly when it is false
(the probability of not making a type 2 error)

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17
Q

What can increase the rate at which statistical signifance is achieved?

A
  • By increasing the sample size
  • By having a smaller standard deviation
18
Q

What can be taken from trials that did not achieve statistical significance?

A

It does not mean there is not a relationship, just that there was not enough evidence to prove that a relationship exists

19
Q

What is the indepandant samples t-test?

A

Used when want to compare the means of two groups

20
Q

What criteria needs to be met before the independant samples t-test can be used?

A
  • There is a random, unbiased sample
  • Data being compared must be continuous
  • Sample must follow normal distribution or have a large enough sample size
  • Need evidence to prove equality of variances
21
Q

How many individuals need to be in a group in order to ignore proving normality?

A

At least 30 in EACH group

22
Q

How do you prove normality in samples?

A

Q-Q plot
Scatterplot of sample quantiles against expected quantiles
If 45* line fits data well= normaility

23
Q

When would you need to prove normailty?

A

When there is < 30 people in each group of the study

24
Q

How do you test for homogenity/equality of variances?

A

Levene’s test

25
Q

What is needed in Levene’s test in order to use the independant sample t test?

A

P value > 0.05
Need to find enough evidence to not reject null hypothesis

26
Q

What is the null hypothesis for Levene’s test?

A

Variances for group 1 = variances for group 2

27
Q

What test is used when there is no evidence of equality of variabilty?

A

Welch’s t-test

28
Q

What can be concluded if the confidence interval contains both negative and positive values?

A

Cannot decide with certainty which group’s mean is higher
Contains 0- not enough evidence to reject null hypothesis and p will be > 0.05

29
Q

How can you decrease the confidence interval?

A

Increase the sample size
Decrease variability between groups

30
Q

What is applied when conducting the independant samples t test on groups with at least 30 people?

A

Central limit theorum- A sufficiency large sample size’s distribution of means approximates to normaility

31
Q

What is parametric and non parametric data?

A

Parametric= normally distributed
Non-parametric= does not follow a normal distribution

32
Q

What test is used instead of the independant sample t-test for non-parametric data?

A

Mann-Whitney U test

33
Q

What are cells, observed frequency, expected frequency and marginal total in contingency tables?

A

Cells= boxes that contain frequencies
Observed frequency= numbers outside bracket
Expected frequency= numbers in the bracket
Marginal total= row and column totals

34
Q

What are the two tests used to analyse contingency tables?

A

Chi squared test
Fishers exact test

35
Q

What does a greater chi squared result mean?

A

Greater overal discrepancies between observed and expected frequencies
Therefore more evidence to reject the Ho

36
Q

What is the continuity correction that can be applied to chi squared tests?

A

Yates correction

37
Q

What does Yate’s correction do to the p value?

A

Reduces value of numerator and therefore the value of chi squared so the p value will rise

38
Q

What is the criticism of Yate’s correction?

A

It is too conservative, risk of false negatives (type II errors)

39
Q

How do you know when to use Chi squared test v Fishers exact test?

A

If 80% of counts in contingency table are of size 5 or more= chi squared
If not = Fishers exact test

40
Q

What is an odds ratio?

A

Statistic that quantifies the strength of association between two events, A and B

41
Q

How are odds ratio calculated?

A
42
Q

Why might odds ratio not always be accurate?

A

The size of the confidence interval will effect it

Sem 1 Year 2 (18 decks)

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