Data Analysis

Question 0

What are the steps for analyzing qualitative data?

Answer 0

1) converting responses into some numerical system or categorical organization
2) tabulation
3) summarize data using descriptive statistics

Question 1

What is the main technique for analyzing qualitative data?

Answer 1

.

Question 2

What are some data analysis strategies?

Answer 2

.

Question 3

Frequencies

Answer 3

The number of times each value of a variable occurs,

Most appropriate for nominal or ordinal variables

Question 4

Measures of central tendency:

Answer 4

mean

mode

median

Question 5

Measures of variability (the spread)

Answer 5

range
quartile deviation
variance
standard deviation
the normal curve
skewed distributions

Question 6

Measures of relative position

Answer 6

percentile ranks
standard scores (z scores, t scores, and stanines)

Question 7

Measures of relationship:

Answer 7

correlation

correlation coefficient

Question 9

What are the two main methods for calculating correlation coefficient?

Answer 9

The Spearman Rho coefficient (for ranked data)

The Pearson r coefficient (for interval and ratio data)

Question 10

The Spearman Rho coefficient (for ranked data)

Answer 10

For correlating ranked data

Question 11

mean

Answer 11

Arithmetic average of all the scores

Question 12

Mode

Answer 12

Most commonly attained score

Question 13

Median

Answer 13

Midpoint in a distribution

Question 14

range

Answer 14

Difference between the highest and lowest score in a distribution

Question 15

quartile deviation

Answer 15

One-half of the difference between the upper quartile (the 75th percentile) and the lower quartile (25th percentile)

Question 16

standard deviation

Answer 16

The square root of the variance (amount of spread between scores)

A measure of variability that is stable and takes into account every score in a distribution.

The most frequently used statistical index of variability.

Question 17

The normal curve

Answer 17

The bell shape formed when a normal distribution is plotted as a frequency graph

Question 18

skewed distribution

Answer 18

Non-symmetric distribution in which there are more extreme scores at on end of the distribution than at the other

Question 19

percentile ranks

Answer 19

Measures of relative position indicating the percentage of scores that fall at or below a certain score.

Question 20

standard scores (z scores, t scores, and stanines)

Answer 20

A derived score that expresses how far a given raw score is from some reference point, typically the mean, in terms of standard deviation units

Question 21

What factors determine the choice of statistical procedures?

Answer 21

Scale of measurement
Method of participant selection
# of groups being compared
# of independent variables

Question 22

What are two assumptions for using a t-test and ANOVA?

Answer 22

The standard deviations (SD) of the populations for all groups are equal (homogeneity of variance)

The samples are randomly selected from the population.

Question 23

What is the purpose of t-test?

Answer 23

Used to determine whether two groups of scores are significantly different at a selected probability level

Question 24

What is the purpose of ANOVA?

Answer 24

Analysis of variance

Used to determine whether scores from two or more groups are significantly different at a selected probability level.

Question 25

What is the difference between t-test and ANOVA?

Answer 25

t-test is appropriate for two groups

ANOVA is appropriate for multiple groups

Question 26

What is the purpose of factor analysis?

Answer 26

It is used to identify relations among variables in a correlation matrix.

Question 27

What is the purpose of chi square?

Answer 27

It used to compare frequencies, percentages, or proportions occurring in different patterns or groups.

Excellent analytical tool for nominal data.

Question 28

How is chi square different from t-test and ANOVA?

Answer 28

Chi square can be used to analyze nominal data,

t-scores and ANOVA cannot.

Question 29

What is the function of multiple regression?

Answer 29

It determines not only whether variables are related, but also the degree to which they are related.

Question 30

What is the purpose of analysis of covariance (ANCOVA)?

Answer 30

Analysis of co-variance is a form of ANOVA that accounts for the different ways in which the independent variables are measured,taking into account the design of the study.

Question 31

What is standard error?

Answer 31

Expected, chance error among means.

Question 32

What are one-tailed tests?

Answer 32

Assumes that a difference can only occur in one direction.

Question 33

Stanine

Answer 33

Standard scores that divide a distribution into nine parts

Question 34

T score (Z score)

Answer 34

A standardized score derived from a z score by multiplying the z score by 10 and adding 50

Question 35

z score

Answer 35

The most basic and most used standard score,

Raw score - mean, divided by the SD

expresses how far a score is from a mean in terms of standard deviation units

Allows scores from different tests to be compared across individuals

Question 36

Variance

Answer 36

Amount of spread between scores

Small variance

Question 37

The Pearson r coefficient (for interval and ratio data)

Answer 37

Most appropriate measure when variables to be correlated are either interval or ratio

Takes into account every score in both distributions

Most stable measure of correlation

Assumes relationship between variables is linear

Question 38

What are two-tailed tests?

Answer 38

Assumes the results can occur in either direction

Question 39

What is a major advantage to one-tailed tests?

Answer 39

It’s statistically “easier” to obtain a significant difference when using a one-tailed test.