Data Analysis In Quantitative Studies

Question 1

What are levels of measurement (or types of data) from least complexity to most?

Answer 1

Nominal level, ordinal level, interval level, ratio level

Question 2

What is nominal level?

Answer 2

• provides info about difference, but not much more
• used to name, identify, or classify into categories

Question 3

What is ordinal level?

Answer 3

• shows direction of difference, but we don’t know amount of difference
• numbers indicate rank or order
  - allows for “greater than” or “less than”
  Ex) podium: know 1st, 2nd, 3rd but not know how much won by

Question 4

What is interval level?

Answer 4

• intervals or distances between numbers are known, but it’s not known how far any of the numbers are from zero
• equality of units, but no true zero
  Ex) Celsius temp scale, know dif +1 to +2 same as +21 to +22
  Can go below 0

Question 5

What is ratio level?

Answer 5

• each number can be thought of as a distance measured from zero
• there is an absolute zero point, represents absence of the variable being measured
  Ex) weight

Question 6

What is nominal and ordinal levels?

Answer 6

Non-parametric data

Question 7

What is the relationship between levels?

Answer 7

Each level has additional characteristic, and contains all the characteristics of the previous one

Question 8

What is interval and ratio levels?

Answer 8

Parametric data

Question 9

What is statistics?

Answer 9

Objective means of interpreting data

Question 10

What 2 things does statistics inform us?

Answer 10

Reliability and meaningfulness

Question 11

What are the most fundamental components of most statistical techniques?

Answer 11

Central tendency and variability (describe data set)

Question 12

What is central tendency?

Answer 12

• single score that best represents all scores for a group of individuals

Question 13

3 ways to measure central tendency?

Answer 13

Mean
Median: number occurring at midpoint of series
Mode: most frequently occurring number

Question 14

What is variability?

Answer 14

Best estimate of the spread of scores

Question 15

How to measure variability?

Answer 15

1) variance
2) standard deviation (square root of variance)

Question 16

What is normal distribution?

Answer 16

Symmetrical around the mean

Question 17

What are 2 other types of distribution?

Answer 17

1) skew mess: scores spread out more on one end of the distribution (positive and negative)
2) kurtosis: peakedness of distribution

Question 18

What are the 2 types of kurtosis?

Answer 18

• Leptokurtic: massive buildup in middle
• Platykurtic: flat distributed across- no building of scores

Question 19

What is correlation?

Answer 19

Measure of the strength of the relationship between two variables, X and Y

Question 20

What is the Pearson r correlation?

Answer 20

A relationship independent of
1) number of scores
2) size of scores
3) dispersion of scores
Derived from covariance

Question 21

What is covariance affected by?

Answer 21

Dispersion of scores

Question 22

What does r= 1.00 or -1.00

Answer 22

Perfect correlation

Question 23

Waht does r = .50 or -.50 mean?

Answer 23

Some overlap of sharing variance

Question 24

What does causal conclusions depend on?

Answer 24

Correlations do not draw basis for causal conclusions, causation depends on methodology, not analysis