Statistical Test Flashcards

(50 cards)

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
What causes differences between absolute risk reduction and relative risk reduction?
Since relative risk reduction is a proportion, you will see bigger results for rare diseases
26
Equation for sensitivity
Number of people who have the disease and test positive divided by the number of people who have the disease
27
Equation for specificity
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
Equation for positive predictive value
Number to test positive who have the disease divided by the number who test positive
29
For negative predictive value
Number of people who test negative and don't have the disease divided by the number of people who test negative
30
Compares One data point or sample mean with the mean of a population of known standard deviation
z test
31
Compares sample mean to a known population mean
Single sample t test
32
Compares means of two distinct samples
Unpaired t-test
33
Compares means of two matched samples
Paired t-test
34
Calculate the effect size
Cohen's d or glass delta
35
Compares means of more than two groups; one independent variable factor and one dependent variable
One Way anova
36
Compare means of more than two groups; two independent variable factors, when dependent variable
Two-way anova
37
Compare means of more than two groups; two or more dependent variables
Manova
38
Control of influence of a covariate in anova test
ANCOVA
39
Correlation between one variable and another; interval or ratio data
Pearson correlation
40
Correlation between one variable and another; ordinal data
Spearman rank order correlation
41
Fit best straight line through a scattergram of linear data
Simple linear regression
42
Fit the straight line through a scattergram of nonlinear data
Simple nonlinear regression
43
Test association between categorical variables by comparing proportions against proportions predicted by theory
Chi-square goodness of fit test
44
Analyze contingency tables of categorical variables for statistical significance
Chi-square test of Independence
45
Analyze 2x2 contingency tables when cell sample size is less than five
Fisher's exact test
46
Analyze contingency table with one category with two levels
Binomial test
47
Analyze contingency table with closely matched samples
McNemar test
48
Compare two unpaired groups, when their data do not have a gaussian distribution
Mann Whitney u test
49
Compare two paired groups when their data do not have a gaussian distribution
Wilcoxon test
50
Anova test that uses ranking
Kruskal Wallace test