# Biostats Week 7 Flashcards

1
Q

µ

A

Mu. Mean of a population or probability distribution

2
Q

t

A

1) a particular probability distribution or 2) a value that obeys that distribution

3
Q

z-score

A

s (standard deviation)

4
Q

s

A

standard deviation

5
Q

µ

A

mean

6
Q

σ

A

Sigma. Standard deviation of a population.

7
Q

m

A

Mean of a sample

8
Q

s^2

A

Sample variance

9
Q

n

A

Number of cases

10
Q

Median

A

score that divides a distribution in half; the mathematical midpoint

11
Q

Mode

A

The value that appears most often during the dataset

12
Q

Bimodal distribution

A

a distribution containing two numeric values that appear with equal frequency

13
Q

Variability

A

extent to which the scores are dispersed around the mean

14
Q

Range

A

difference between the highest and lowest values in a distribution

15
Q

Deviations from the mean

A

calculated by subtracting the mean from a given score; sum of the deviations will always equal zero

16
Q

Mean deviation

A

Sum of mathematically absolute deviations from the mean of the distribution

17
Q

Variance

A

equal to the standard deviation squared

18
Q

Standard deviation

A

Standard deviation: square root of the variance

s=standard deviation for sample, σ=standard deviation for a population

19
Q

Z/Z-score

A

Z (Z Score): point along the baseline of a standardized normal curve

20
Q

Hypothesis

A

Hypothesis: statement of expectations

21
Q

Null hypothesis

A

Null hypothesis: statement of equality; statement of no difference; statement of chance

22
Q

Critical value

A

Critical value: point on a distribution that marks the beginning of the critical region; point of comparison when making decision about null hypothesis

23
Q

Calculated test statistic

A

Calculated test statistic: result of a hypothesis-testing procedure; value that is compared to critical value

24
Q

Critical region

A

Critical region: portion of distribution that contains all the values that allow you to reject the null hypothesis; also known as region of rejection

25
Q

Type I Error

A

Type I error: rejection of the null hypothesis when it is in fact true

26
Q

Type II Error

A

Type II error: failure to reject the null hypothesis when it is false

27
Q

Single sample with sigma unknown

A

Single sample with sigma unknown: standard error of the mean is estimated and t is used

28
Q

Single sample with sigma known

A

Single sample with sigma known: standard error of the mean is calculated in a direct fashion and Z is used

29
Q

t-statistic

A

Used when we do not know the standard deviation of the population mean.

30
Q

How to calculate t

A

(Sample std dev/√(sample size))

31
Q

Matched samples (related):

A

Samples selected in such a way that cases included in one sample are related to cases in another (before & after sampling, etc)

32
Q

Standard error of mean difference:

A

Standard deviation of repeated sampling of mean differences between scores reflected in 2 samples

33
Q

A nurse researcher wishes to determine if there is a difference in the mean serum phosphorus level for a random sample of clients who have puritis and a random sample of clients who do not have puritis. What would be an appropriate test?

A

t-test for independent groups

34
Q

Your study includes an alpha of 0.05 and a power of 0.80. You conduct a student t-test, which has a large sample and a p-value of 0.04. What type of error might you make?

A

Type I

35
Q

In order to calculate the necessary sample size for your study you will need to know:

A

Effect size

Power

36
Q

You are asked to design a study determining whether there is a difference in the average fasting blood glucose for individuals with diabetes randomized either to a strictly dietary intervention or to a diet and exercise intervention. What are you investigating?

A

Difference

37
Q

If you select an alpha of 0.05 and a power of 0.80 for your study and your independent t-test for the difference in the mean serum potassium level of kidney dialysis patients and kidney transplant patients has a p-value of 0.02. You know this means:

A

There is a significant difference between the 2 groups

38
Q

Your study includes an alpha of 0.05 and a power of 0.80. You conduct a student t-test, which has a p-value of 0.07. What type of error might you make?

A

Type II

39
Q

How does effect size increase statistical power?

A

The smaller the effect size the more overlap between our distributions and the lower the statistical power.

40
Q

You conduct a study to determine if there is a difference in average number of hours slept each week between husbands and wives.What would be an appropriate test?

A

t-test for independent groups

41
Q

The following is a NONDIRECTIONAL hypothesis.

The relationships among gender identity, religiosity, and social actions are weaker among Arab women than among Jewish women.

A

FALSE

42
Q

You anticipate a large effect size in your study, therefore you will need a large sample size.

A

FALSE