Vocab

Question 1

Confidence Interval:

Answer 1

interval or range of values centered around a sample statistic. The logic behind a confidence interval is that a sample statistic, such as sample mean should be relatively near to the corresponding population parameter.

Question 2

ANOVA

Answer 2

Hypothesis testing procedure that is used to evaluate mean differences between two or more treatments (or populations)

Question 3

F-ratio

Answer 3

test statistic for analyses of variances;
compares differences (variance) between treatments w/ differences that are expected.

Question 4

F-distribution

Answer 4

all possible F values when Ho is true

Question 5

Logic of Anova

Answer 5

B(variance)/W(variance)=F

Question 6

Within group variance

Answer 6

difference that exists inside each treatment condition

Question 7

between group variance

Answer 7

value used to measure and describe between treatments mean differences

Question 8

Independent Variable:

Answer 8

manipulated by the researcher

Question 9

Levels of Independent Variable:

Answer 9

2 levels. The two different situations, environments, etc.

Question 10

Dependent Variable:

Answer 10

What is being measured.

Question 11

59. Normal Distribution:

Answer 11

The mean, median, and mode of a normal distribution are equal and defined by two parameters, the mean (μ) and the standard deviation (σ).

Question 12

60. Probability of Occurrence:

Answer 12

For a situation in which several different outcomes are possible, the probability for any specific outcome is defined as a fraction or a proportion of all the possible outcomes. If the possible outcomes are identified as A, B, C, D, and so on, then Probability of A = #of outcomes classified as A/ Total # of possible outcomes

Question 13

61. Statistical Significance:

Answer 13

it is very unlikely to occur when the null hypothesis is true. That is, the result is sufficient to reject the null hypothesis.

Question 14

62. Significant Difference:

Answer 14

when p < .05

Question 15

64. Null Hypothesis:

Answer 15

states that in the general population there is no change, no difference, or no relationship. In the context of an experiment, predicts that the independent variable (treatment) has no effect on the dependent variable (scores) for the population.

Question 16

65. Research Hypothesis:

Answer 16

your prediction on what you believe the difference to be.

Question 17

66. Directional Hypothesis:

Answer 17

Predicting direction of the difference.

Question 18

67. Non-Directional Hypothesis

Answer 18

: Predict difference, but no direction. Ex. “This group will score different than the other”

Question 19

68. Reference Distribution:

Answer 19

used if deviations of the estimated parameter in either direction from some benchmark value are considered theoretically possible

Question 20

69. One-Tailed Test:

Answer 20

used if only deviations in one direction are considered possible

Question 21

70. Two-Tailed Test:

Answer 21

used if deviations of the estimated parameter in either direction from some benchmark value are considered theoretically possible

Question 22

71. Critical Region:

Answer 22

It is the area, or areas, of the sampling distribution of a statistic that will lead to the rejection of the hypothesis tested when that hypothesis is true.

Question 23

72. Cutoff Value:

Answer 23

where only those p-values less than or equal to the cutoff will result in rejecting null hypothesis.

Question 24

73. Region of Rejection:

Answer 24

range of values that leads the researcher to reject the null hypothesis

Question 25

74. Reject Null:

Answer 25

P < .05

Question 26

75. Fail to Reject Null:

Answer 26

P > .05

Question 27

76. Alpha:

Answer 27

alpha 05 is how significance is determined

Question 28

05 Criterion:

Answer 28

p-value must be less than this for significant difference

Question 29

79. Between-Subjects Design (Independent Measures):

Answer 29

A research design that uses a separate sample for each treatment condition or each population being compared.

Question 30

81. Within Subjects Design:

Answer 30

1 group testing two different things such as before and after something

Question 31

85. SPSS interpretation:

Answer 31

put in on SPSS and get the results

Question 32

86. Results:

Answer 32

(APA format)

Question 33

87. Power:

Answer 33

of a statistical test is the probability that the test will correctly reject a false null hypothesis. That is, power is the probability that the test will identify a treatment effect if one really exists.

Question 34

90. Type I Error:

Answer 34

when a researcher rejects a null hypothesis that is actually true

Question 35

91. Type II Error:

Answer 35

when a researcher fails to reject a null hypothesis that is really false

Question 36

92. Effect Size:

Answer 36

is intended to provide a measurement of the absolute magnitude of a treatment effect, independent of the size of the sample(s) being used.

Question 37

Omnibus F test

Answer 37

any statistical test in which the test statistic has an F-distribution under the null hypothesis

Question 38

Tukey’s HSD test

Answer 38

A test that allows you to compute a single value that determines the minimum difference between treatment means that is necessary for significance. A commonly used post hoc test.

Question 39

post hoc tests

Answer 39

A test that is conducted after an ANOVA with more than two treatment conditions where the null hypothesis was rejected. The purpose of post hoc tests is to determine exactly which treatment conditions are significantly different.

Question 40

LSD

Answer 40

least significant difference