HCM 360- Section 4

Question 1

inferential statistics

Answer 1

used to draw conclusions about what’s likely true in a larger population based on findings from a sample

Question 2

Descriptive Statistics

Answer 2

characterize sample itself

Question 3

Define Ordinal Measurement

Answer 3

data that are measured by categories imply order (i.e. clothing size, military rank); consistent in direction; defines a total preorder of objects; the scale values themselves have a total order

Question 4

Define ratio measurement

Answer 4

data that have differences that are meaningful and relate to some true zero point (i.e. weight, height, age); most common scale of measurement

Question 5

Define interval measurement

Answer 5

data if the difference between values have meanings (i.e. temperature)

Question 6

Define Nominal measurement

Answer 6

data used when each case is classified into one of a number of discrete categories i.e. color, political party, gender; “Naming” level

Question 7

What are the measures of central tendency?

Answer 7

Mean, Median, and Mode (NOT RANGE)

Question 8

Define Mean

Answer 8

the arithmetic average of a set of values, or distribution; most common measure of central tendency; can be applied to interval data

Question 9

Define Median

Answer 9

score that divides distribution into two equal parts so that half the cases are above it and half are below it; represents exact center/middle of distribution; appropriate for variables at ordinal level; described as the number separating the higher half of a sample, a population, or a probability distribution, from the lower half. The value below, which lies 50% of the data; can be applied to ordinal, interval data; not nominal

Question 10

Define Mode

Answer 10

the values that occurs with the greatest frequency in a set of data; can be applied to nominal, ordinal, interval data

Question 11

Considering the numbers 3,10,4,9,5,2 and 9, what is the median?

Answer 11

5

Question 12

What are the measures of variation?

Answer 12

variance, standard deviation, and range

Question 13

Define Range

Answer 13

the difference between the largest and smallest values in a given set of data; measure of variation

Question 14

Define Variance

Answer 14

the amount to which each object differs

Question 15

Define Standard Deviation

Answer 15

describes the variability of the sample; how much participants vary or differ from each other

Question 16

Skewness

Answer 16

a skew is positive if it is skewed to the right. A skew is negative if it is skewed to the left.

Question 17

Normal distribution

Answer 17

a bell curve

Question 18

Collectively exhaustive

Answer 18

when a set of data includes all of the possible observations without missing any values. An example would be choosing African American and White when there are Hispanics in a data set.

Question 19

Mutually exclusive

Answer 19

an observation is assigned one and only one category. Example would be hospitals grouped by type.

Question 20

T-test and Simple one-way ANOVA

Answer 20

The t-test is used when determining if two averages or means are the same or different. The ANOVA is preferred if comparing three or more averages or means. A t-test has more odds of committing an error the more means are used which is why ANOVA is used when comparing two or more means.

Question 21

Linear Regression

Answer 21

an approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables (or independent variables) denoted X

Question 22

Dr. Evens was surprised that many of his participants scored much lower than expected on his post-test. When he observed a significant increase in score on the pre-test, he was cautious in attributing the effect to his treatment alone. Which of the following threats to internal validity was Dr. Evans concerned about?
A) Instrumentation
B) Selection
C) Regression
D) Testing

Answer 22

C) Regression

Question 23

When a set of data includes all of the possible observation without missing any values, it is know as

Answer 23

Being collectively exhaustive

Question 24

Which of the following variables is an example of the nominal level of measurement?
A) Rank in grad class
B) Gender
C) age of students
D) Amount of money earned

Answer 24

B) Gender

Question 25

Null hypothesis

Answer 25

states an assumption to be tested; rejecting a null hypothesis after observing a test statistic which exceeds the critical value at the .05 level means that there is a 5% chance that the null hypothesis is actually true

Question 26

Non-directional hypothesis

Answer 26

a non-directional research hypothesis reflect a difference between groups, but the direction of the difference is not specified. We do not suppose that one is higher than the other.

Question 27

Directional hypothesis

Answer 27

a direction research hypothesis reflects a difference between groups, and the direction of the difference is specified. This represents an equality but not of a specific nature

Question 28

If Dr. Robinson rejects the null hypothesis after observing a test statistic which exceeds the critical value at the .05 level, there is ________

Answer 28

A 5% chance that the null hypothesis is actually true

Question 29

Type I Error

Answer 29

The probability of rejecting a null hypothesis when it is true. Usually 0.05 or p < .05. Whenever p-value is less than alpha, always reject the null/ accept the research.

Question 30

Type II Error

Answer 30

The probability of failing to reject a null hypothesis when it is false. Example: There really is a significant difference in a given population, but you do not find the difference in your sample and thus determine that there is no significant difference (thus you fail to reject a false null). As your sample characteristics become closer to the population, the probability that you will accept a false null hypothesis decreases. Whenever the p-value is higher, you reject the research hypothesis and accept the null.

Question 31

Which is an example of ordinal scale measurement?

Answer 31

Freshman (in school; sophomore, junior, senior)