Exam 1 Flashcards

1
Q

Definition of p-value: (2)

A

The probability that our results are due to chance alone. The probability of making a type 1 error.

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2
Q

How is p-value used to determine whether to accept or reject the null hypothesis?

A

P-value is compared to alpha=0.05 to determine whether to accept or reject it. If “p” is less than or equal to 0.05 than we reject the null hypothesis, and we accept if greater than 0.05.

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3
Q

What is statistical power?

A

Statistical power is the probability of successfully rejecting the null hypothesis.

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4
Q

Increasing “n” will ____ power

A

Increase

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5
Q

Give 2 reasons why it is not possible for researchers to study an entire population

A
  1. It would take too much resources to study an entire population.
  2. There are usually too many subjects in a population to be able to gather them for a study.
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6
Q

What is a type 1 error?

A

A type 1 error is when you reject the null hypothesis but you should have accepted it because its true.

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7
Q

What is standard deviation a measure of?

A

Standard deviation is a measure of how data points, x, differ from the mean, (bar X).

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8
Q

What is random assignment and what is one advantage of using it?

A

Giving participants in a study an equal probability of being assigned to a certain group. One advantage is that it gets rid of some bias.

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9
Q

Which of the following is not a measure of sampling error?

a. Confidence limits
b. Power
c. Standard error
d. None of the above

A

b. Power

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10
Q

Describe 95% confidence limits

A

A researcher is 95% confident that the population mean is within the confidence limits.

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11
Q

On what axis is the independent variable plotted?

A

Horizontal

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12
Q

Which three measures are approximately equal in a normal distribution?

A

Mean, Median, and Mode

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13
Q

What type of statistical analysis should be used to compare observed phenotypic frequencies for a dihybrid cross involving eye color (red, white) and wingless (wildtype or wingless) to an expected ratio of 9:3:3:1?

A

Chi Square Goodness of Fit

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14
Q

How is Z-score Calculated?

A

(“x” - mean)/Standard deviation

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15
Q

In the tattoo hepatitis test, what type of statistic test should be used to analyze the data?

A

Chi square test of Independence

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16
Q

What is the null hypothesis for the hepatitis/tattoo case?

A

Hepatitis C is not dependent on the tattoo parlor.

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17
Q

What is the alternative hypothesis for the hepatitis/tattoo case?

A

Hepatitis C is related to the tattoo parlor.

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18
Q

What are three examples of categorical variables?

A

Gender, Phenotype, Genotype

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19
Q

What are three examples of numerical variables?

A

Height, Age, Biomass

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20
Q

What two things must a histogram have?

A

Measured variable on x-axis, and frequency on y-axis

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21
Q

What is gaussian distribution?

A

When the mean, median, and mode are all equal. Normal bell shape curve.

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22
Q

How is range calculated?

A

Highest-Lowest

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23
Q

How is variance calculated?

A

(Standard Deviation)^2

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24
Q

How is the mode of a graph recognized?

A

Always the highest peak

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25
Q

What do positive and negative skew look like on a graph?

A

Neg. Skew has a tail on the left, and pos. skew has a tail on the right

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26
Q

Describe Symmetric Distribution

A

50% of the data is above the mean, and 50% of the data is below the mean

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27
Q

What is sampling error?

A

How much in error of the population we are by studying the sample.

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28
Q

What can influence sampling error?

A

-Anomalies: Subjects that differ greatly from the mean

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29
Q

What is the standard error of the mean?

A

How much our sample mean is different from the population mean.

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30
Q

What are 3 ways to lower standard error?

A
  • Increase the sample size
  • Decrease the standard deviation
  • Improve measurement
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31
Q

What do two sample t-tests test for?

A

To determine whether the difference between two sample means is statistically significant.

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32
Q

What is meant by “Statistically significant”?

A

More than we’d expect by chance

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33
Q

How do you decide if a 2-sample t-test or a paired t-test should be conducted?

A

If the experiment can’t be performed twice, then a 2-sample t-test must be used. Otherwise use a paired-t-test

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34
Q

What 2 things does a 2-sample t-test assume?

A
  • The data for each sample is normally distributed

- The variances for each sample are statistically equal

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35
Q

What 1 thing does a paired t-test assume?

A

The differences between pairs of data are normally distributed

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36
Q

What is a type 2 error?

A

When you accept the null hypothesis but should have rejected it.

37
Q

What is the non-parametric alternative test to a 2-sample t-test?

A

Kruskal-Wallis Test

38
Q

What is the non-parametric alternative test to a paired t-test?

A

Wilcoxon Signed Rank test

39
Q

What is an advantage of random sampling?

A

Eliminates some bias

40
Q

What is the difference between a bar graph and a histogram?

A

Bar Graph: Shows categorical data on the x-axis and a d.v. on the y-axis
Histogram: Shows numerical data on the x-axis and frequency on the y-axis

41
Q

What are the three measures of central tendency?

A

Mean, median and mode

42
Q

In a Z-test, what is the null hypothesis compared to?

A

0.025 instead of 0.05

43
Q

When is welch’s approximation used?

A

For samples with unequal variances, as a nonparametric alternative to the 2-sample t-test

44
Q

What is the difference between a parametric and non-parametric test?

A

A parametric test makes assumptions about the population that must be met in order to conduct the test, such as homogeneity of variances or normalized data. Whereas a nonparametric test does not make assumptions about the population.

45
Q

What is the nonparametric alternative to a 2-sample t-test that does not meet the assumption of normality?

A

Mann-Whitney U-Test

46
Q

What is the nonparametric alternative to a 2-sample t-test that does not meet the assumption of equal variances?

A

Komolgrov-Smirnov Test

47
Q

What nonparametric test determines homogeneity of variances?

A

Levene’s Test

48
Q

Why is 1-way ANOVA better than multiple t-tests?

A

Designed to protect against alpha inflation, aside from saving time unnecessarily spent conducting multiple tests. Reducing alpha inflation lessens the chance of receiving a false positive.

49
Q

What is the nonparametric alternative to One Way ANOVA?

A

Kruskal-Wallis Test

50
Q

What is the difference behind the purpose of correlation and the purpose of linear regression?

A

Correlation analysis specifically tests for a linear relationship between 2 measured independent variables and a measured dependent variable. Regression attempts to fit a line, or curve, to data to look for a dependence of one variable on another.

51
Q

Describe the F-Ratio

A

Compares the variation between each group being tested, relative to the variation between individuals within each group. A large F-Ratio indicates more variation between groups relative to the variation within groups

52
Q

“2 x 3” design is:

A

Comparing means of 2 independent variables, 1 with 2 levels and 1 with 3 levels. giving a total of 6 groups

53
Q

Main Effect:

A

Explains whether the effect of an independent variable on a measured dependent variable is significant or not

54
Q

Interaction:

A

Explains if two independent variables influence one another in their effect on the dependent variable

55
Q

What “r” values represent a strong correlation?

A

Absolute values closer to “1”

56
Q

What is the main assumption of repeated measures ANOVA?

A

Sphericity: The variances of all possible pairwise combinations of groups are equal

57
Q

How are 2-way ANOVA results reported?

A

F(2,84)=15.75, p

58
Q

How are regression results reported?

A

B=0.287, p

59
Q

How is a regression equation set up?

A

Dependent=B value(for I.V.) x I.V. + B value (for D.V.)

60
Q

GO INTO DETAIL WITH SPECIFIC CONCLUSIONS

A

GO INTO DETAIL WITH SPECIFIC CONCLUSIONS

61
Q

What do you do after calculating a Z score?

A

Compare it to the value in the table to find your p-value, then compare that to 0.025

62
Q

How are chi-square results reported?

A

X2(1)=2.251, p=0.134

63
Q

How do you calculate degrees of freedom for chi-square?

A

of categories - 1

64
Q

How is the chi-square value compared to the critical value?

A

If the calculated value is higher than the critical value, then our p-value is higher than 0.05 so we reject the null hypothesis.

65
Q

What does multiple regression look at?

A

Whether “y” depends on any of the MULTIPLE independent variables

66
Q

How does simultaneous multiple regression work?

A

All I.V.’s are analyzed at the same time to give an overall R squared value, as opposed to step-wise multiple regression in which each I.V. gets its own R squared value

67
Q

What result should be examined when interpreting step-wise multiple regression results?

A

The column on the right tells us if the change in R squared is significant or not

68
Q

How is chi-square test of independence different from correlation?

A

It analyzes 2 or more CATEGORICAL variables with counted FREQUENCIES to determine if they are related

69
Q

What is an example of a test of independence?

A

Is prostate cancer outcome dependent on the type of treatment? (categories are surgery and radiation)

70
Q

How are correlation results reported?

A

r(18)= 0.254, p=0.280

71
Q

How are degrees of freedom calculated for correlation problems?

A

n-2

Ex: sample of 20-2=18

72
Q

When should you use a line graph?

A

When variable on x-axis is numerical, not categorical

73
Q

What does each dot on a line graph represent?

A

A different mean

74
Q

What must line graphs with 2 I.V.s have?

75
Q

What do asterisks indicate on a bar graph?

A

Which comparisons are significant, N.S. = Not significant

76
Q

What does a scatterplot look like? When are they mostly used?

A

Variables on both axes are numerical, ALL the raw data are plotted. Used with small sample sizes. A measurement of X and a measurement of Y make a dot on the graph that shows trends and relationships

77
Q

Which graph lacks error bars, bar graph or histogram?

A

Histogram because we are plotting counts, not means

78
Q

When is a table used?

A

When there are too many statistical results to report in an analysis or show in a graph.

79
Q

What 4 other depictions can be used to show data?

A

Photographs, flowcharts, diagrams, and maps

80
Q

How is “and” probability calculated?

A

Prob. of “A x B”

Ex: Flipping a coin to get heads twice= 1/2 x 1/2 = 1/4

81
Q

How is “or” probability calculated?

A

Prob. of “a” + “b”

Ex: Rolling a 2 OR a 3= 1/6 + 1/6 = 2/6 = 1/3

82
Q

How are “at least” probability problems calculated?

A

Find lesser probability and subtract from 1
Ex: At least 1 coin comes up heads=
Both tails is 1/2 x 1/2 = 1/4 , 1 - 1/4 = 3/4 = 75%

83
Q

How do you determine if a study is real?

A

Replicate the experiment and see if you get the same results

84
Q

Define Validity

A

The extent to which a measure actually indicates what i’s intended to

85
Q

Peer-Reviews don’t…….

A

Protect against falsified data

86
Q

List three ways a report could be inadequate or false by lying with statistics:

A
  1. Sample size unrepresentative/small/biased
  2. Inadequate controls/comparisons
  3. Non-randomized
87
Q

What is the problem with non-random studies?

A

Could be biased allocation of patients to certain groups

88
Q

What is regression used for?

A

Predicting an equation of “Y” based on “X”

89
Q

What is the difference between the chi square test of independence and the goodness of fit test?

A

The test of independence uses categorical variables to find a relationship between them, while the goodness of fit test looks to see if observed frequencies match what is expected by chance alone.