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Clinical Biostat And Epi > Statistical Test > Flashcards

Statistical Test Flashcards

1
Q

Number of standard deviations s that a data point on a curve lies from the curves mean

A

Z score

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2
Q

What type of statistics is a z score used for?

A

Descriptive

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3
Q

interval which is expected to typically contain the parameter being estimated

A

Confidence interval

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4
Q

What does the confidence interval depend on?

A
  1. Sample size
  2. Size of the standard deviation
  3. Degree of confidence that you want
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5
Q

What does the p value depend on

A
  1. Difference between the means that are being compared
  2. The standard deviation of the sample
  3. The size of the sample
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6
Q

number, calculated from a statistical test, that describes how likely you are to have found a particular set of observations if the null hypothesis were true

A

P value

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7
Q

What is the advantage of using a confidence interval?

A

Gives you a meaningful range of means to look at which augments the information of the p-value

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8
Q

What is the benefit of using a p-value

A

Gives you a single probability but can be very specific about the size of the probability

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9
Q

Regardless of the shape of a population curve you will get a normal curve if you take numerous repeated random samples of a set size from the population and plot the means of those samples.

A

central limit theorem

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10
Q

What does a very small standard error of the mean suggest?

A

That the sample mean is close to the population mean

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11
Q

The ____ this sample size (n), the ____ the standard error of the mean and narrower the curve

A

Larger… Smaller

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12
Q

Standard error of the mean versus standard deviation

A

Standard deviation measures the spread of the data

Standard error of the mean measures how well you know the population mean

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13
Q

Interpretation of a 95% confidence interval

A

You can be 95% sure that the true population mean lies within the 95% confidence interval

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14
Q

Used to compare one data point with a known population whose mean and standard deviation are known

A

Z score

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15
Q

Used to compare a sample mean that the known population is mean and standard deviation are known

A

Z test

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16
Q

Test used to compare means when the population standard deviation is unknown (which is typically the case)

A

T test

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17
Q

Compares a sample mean to a known population mean (like comparing the stressful sample mean with the mean of the US population)

A

Single sample t test

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18
Q

This test compares two distinct samples (like comparing Chesterfield sample with the sample from neighboring worry town )

A

Independent samples t-test or unpaired t-test

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19
Q

This type of test compares two matched samples ( like comparing the stressful sample with the same stressful people the previous year)

A

Dependent samples t-test or paired t-test

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20
Q

Give at least one example of when you would use a paired t-test

A

1 comparing the before and after of a treatment on a single patient
2. Comparing treatment on one side of the body with the other in a single patient
3. Comparing one twin with the other
4. Close matching of two different groups for many variables such as age, gender, cultural and economic background, medical history, education, and area of residence

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21
Q

Is the smaller or larger sem desired? Why?

A

Smaller, the smaller the SEM, the smaller the confidence interval and more certain the population mean

22
Q

Incidence of a disease progression in people taking the placebo minus the incidence of disease progression in people taking the treatment

A

Absolute risk reduction

23
Q

The incidence of disease attributed to the risk factor minus the incidence of disease in persons not exposed to the risk factor

A

Attributable risk

24
Q

1 - the relative risk

A

Relative risk reduction

25
Q

What causes differences between absolute risk reduction and relative risk reduction?

A

Since relative risk reduction is a proportion, you will see bigger results for rare diseases

26
Q

Equation for sensitivity

A

Number of people who have the disease and test positive divided by the number of people who have the disease

27
Q

Equation for specificity

A

Number of people who do not have the disease and test negative divided by the number of people who do not have the disease

28
Q

Equation for positive predictive value

A

Number to test positive who have the disease divided by the number who test positive

29
Q

For negative predictive value

A

Number of people who test negative and don’t have the disease divided by the number of people who test negative

30
Q

Compares One data point or sample mean with the mean of a population of known standard deviation

A

z test

31
Q

Compares sample mean to a known population mean

A

Single sample t test

32
Q

Compares means of two distinct samples

A

Unpaired t-test

33
Q

Compares means of two matched samples

A

Paired t-test

34
Q

Calculate the effect size

A

Cohen’s d or glass delta

35
Q

Compares means of more than two groups; one independent variable factor and one dependent variable

A

One Way anova

36
Q

Compare means of more than two groups; two independent variable factors, when dependent variable

A

Two-way anova

37
Q

Compare means of more than two groups; two or more dependent variables

A

Manova

38
Q

Control of influence of a covariate in anova test

A

ANCOVA

39
Q

Correlation between one variable and another; interval or ratio data

A

Pearson correlation

40
Q

Correlation between one variable and another; ordinal data

A

Spearman rank order correlation

41
Q

Fit best straight line through a scattergram of linear data

A

Simple linear regression

42
Q

Fit the straight line through a scattergram of nonlinear data

A

Simple nonlinear regression

43
Q

Test association between categorical variables by comparing proportions against proportions predicted by theory

A

Chi-square goodness of fit test

44
Q

Analyze contingency tables of categorical variables for statistical significance

A

Chi-square test of Independence

45
Q

Analyze 2x2 contingency tables when cell sample size is less than five

A

Fisher’s exact test

46
Q

Analyze contingency table with one category with two levels

A

Binomial test

47
Q

Analyze contingency table with closely matched samples

A

McNemar test

48
Q

Compare two unpaired groups, when their data do not have a gaussian distribution

A

Mann Whitney u test

49
Q

Compare two paired groups when their data do not have a gaussian distribution

A

Wilcoxon test

50
Q

Anova test that uses ranking

A

Kruskal Wallace test

Clinical Biostat And Epi (6 decks)

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