Ch. 11 Exam 2

Question 1

Theory addressing statistical analysis from the perspective of the extent of a relationship or the probability of accurately predicting an event. If probability is 0.23, then p = 0.23. There is a 23% probability that a particular event will occur. Probability is usually expected to be p < 0.05 or p < 0.01.

Answer 1

probability theory

Question 2

Theory based on assumptions associated with the theoretical normal curve. Used in testing for differences between groups, with the expectation that all the groups are members of the same population. The expectation is expressed as a null hypothesis, and the level of significance (alpha) is often set at 0.05 before data collection.

Answer 2

decision theory

Question 3

A theoretical frequency distribution of all possible values in a population. In a normal distribution curve, the mode, median, and mean are =. Levels of significance and probability are based on the logic of the normal curve. In research, the probability that any data score will be within a certain range of a mean values is calculated based on the theory of the normal curve.

Answer 3

normal curve

Question 4

2 tailed test of significance = the analysis of nondirectional hypothesis. One tailed test of significance = the analysis of directional hypothesis. One tailed statistics test are uniformly more powerful than 2 tailed test.

Answer 4

tailedness

Question 5

the risk of a type II error can be determined using power analysis (1-B).

Answer 5

power

Question 6

describes or summarize the sample and variables.

Answer 6

descriptive statistics

Question 7

ungrouped frequency distributions. Grouped frequency distributions. % distributions.

Answer 7

frequency

Question 8

Grouped Frequency Distributions. Example: data are pre-grouped into categories.

Answer 8

Ages 20 - 39: 14
Ages 40 - 59: 43
Ages 60 - 79: 26
Ages 80 - 100: 4

Question 9

% distribution. Example:

Answer 9

Salaries: 41.7%
Maintenance: 8.3%
Equipment: 16.7%
Fixed cost: 8.3%
Supplies: 25%

Question 10

Ungrouped Frequency distributions: Example: data are presented in raw, counted form.

Answer 10

1. I
2. IIIII
3. III
4. I
5. II

Question 11

Measures of Central Tendency

Answer 11

Mean
Median
Mode

Question 12

is the numerical value or score that occurs with greatest frequency.

Answer 12

mode

Question 13

is the midpoint or the score at the exact center of the ungrouped frequency distribution—the 50th percentile

Answer 13

median

Question 14

is the sum of the scores divided by the number of scores being summed.

Answer 14

mean

Question 15

Is obtained by subtracting lowest score from highest score. Uses only the two extreme scores. Very crude measure and sensitive to outliers

Answer 15

ranges

Question 16

Indicates the spread or dispersion of the scores

Answer 16

Variance

Question 17

is the square root of the variance. Mean = average value. SD = average difference score.

Answer 17

standard deviation

Question 18

Raw scores that cannot be compared and are transformed into standardized scores. Common standardized score is a Z-score. Provides a way to compare scores in a similar process. Ex: children’s BMI

Answer 18

standardized scores

Question 19

Have 2 scales: horizontal axis (X) and vertical axis (Y). Illustrate a relationship between 2 variables.

Answer 19

scatterplots

Question 20

Frequency:

Answer 20

group freq distributions
% distribution
ungrouped freq distributions

Question 21

infer or address objectives, ?’s, and hypotheses. Assist in: identifying relationships, examining predictions, and determining group differences in studies.

Answer 21

inferential statistics

Question 22

inferential statistics:

Answer 22

Examining differences
Predicting outcomes
Examining relations

Question 23

test for significant differences between 2 samples. Most commonly used test of differences. Example: t = 4.169 (p <0.05)

Answer 23

t-test

Question 24

test for differences between variance. More flexible than other analyses in that it can examine Data from 3 or more. If there are more than 2 groups under study, it is not possible to determine where the significant differences are. Post hoc test are used to determine the location of differences.

Answer 24

ANOVA

Question 25

used with nominal or ordinal data. Test for differences between expected frequencies if groups are alike and frequencies if groups are alike and frequencies actually observed in the data. Indicate that there is a significant difference between some of the cells in the table. The difference may be between only 2 of the cells, or there may be differences among all of the cells. Chi-square results will not tell you which cells are different. Ex: x2 = 4.98, df = 2, p = 0.05.

Answer 25

chi-squared test

Question 26

used when 1 wishes to predict the value of the 1 variable based on the value of 1 or more other variables.

Answer 26

predicting outcomes (regression)

Question 27

Examining relationships
Test for the presence of a relationship between 2 variables.
Results: nature of the relation (pos or neg), magnitude of the relation (-1 or +1) and testing the significance or a correlation coefficient.
Does not identify direction of a relationship ( 1 variable does not cause the other). They are symmetrical. Test for the presence of a relation between 2 variables.

Answer 27

Pearson product-moment correlation

Results:
R2 = 0.56 (p = 0.03)
R2 = -0.13 (p = 0.2)
R2 = 0.65 (p< 0,002) —> SIGNIFICANT

Question 28

Using statistics to describe:

Answer 28

Descriptive statistics are also referred to as summary statistics. In any study which the data are numerical, data analysis begins with descriptive statistics. In simple descriptive studies, analysis may be limited to descriptive statistics.