Exam 2 - Handout 5

Question 1

What is QUALITATIVE data? Example?

Answer 1

Meaningful information collected in words

Not typically used for healthcare research w/ large populations

Ex. Written observation in medical records

Question 2

What is QUANTITATIVE data? Examples?

Answer 2

Numerical/countable information

Ex. Age, weight, BP

Question 3

What are discrete variables? Examples?

Answer 3

• Categorical
• Have a few possible values
• Often defined as “counts”

Ex. Sex, number of hospitalizations, yes/no

Question 4

What are continuous variables?

Answer 4

Exist on a defined scale

Ex. Age, body temp, weight

(Think number lines)

Question 5

What are the levels of measurement?

Answer 5

Nominal data
Ordinal data
Interval data
Ratio data

Question 5

nominal data

Answer 5

Discrete categories with no particular order (e.g., sex)

(NOminal = NO order)

Question 5

ordinal data

Answer 5

Discrete categories that can be ranked

e.g., Likert-type questions, pain scales

(likert-type questions are ones where you answer with “agree” “strongly disagree”)

(ORDinal = in ORDer)

Question 6

interval data

Answer 6

continuous data with:
- a defined scale
- constant intervals

DOES NOT HAVE A TRUE ZERO POINT (this is what makes it different from ratio data)

ex. temperature (because even if the temp is 0, there is still a temp)

Question 7

ratio data

Answer 7

continuous data with:
- defined scale
- constant intervals
- true zero point

ex. age, weight, income

Question 8

Independent variable

Answer 8

The variable hypothesized to explain an observed clinical phenomenon

Think of it as the cause

Question 8

Dependent variable

Answer 8

Variable that is predicted/explained by the independent variable

Think of it as the effect

Question 9

Control variables

Answer 9

Other explanatory variables included to hold external conditions constant and isolate the effect of the independent variable

Question 10

Measures of central tendency

Answer 10

Mean
Median
Mode

Question 11

Mean

Answer 11

Arithmetic average of a set of values

Question 12

Median

Answer 12

The middle value when data is arranged in order

Preferred when data has outliers that skew the mean

Question 13

Mode

Answer 13

The value that appears most often

Useful for non-numerical, categorical values

Question 14

Measures of dispersion

Answer 14

Range
Interquartile range
Variance of standard deviation
Skewness

Question 15

Interquartile range

Answer 15

The difference between the 75th and 25th percentiles

Represents the middle 50% of the data

Question 15

Range

Answer 15

The difference between the highest and lowest values

Question 16

Variance

Answer 16

Represented by σ²

The average squared distance of values from the mean

(SD/mean)

Question 17

Standard deviation

Answer 17

Represented by σ

The square root of the variance

Question 17

Skewness

Answer 17

Indicates if data are evenly distributed around the mean

Question 17

Coefficient of variation (CV)

Answer 17

Standardized measure of dispersion

σ/μ

Question 18

Positive skew

Answer 18

More data concentrated to the LEFT of the mean

Question 19

Negative skew

Answer 19

More data concentrated to the right of the mean

Question 20

Box plots

Answer 20

Visually display the range, IQR, and median of a variable

Useful for comparing distributions across groups

Question 20

Frequency tables

Answer 20

Organize discrete or continuous data by counting the frequency of each value

Should include clear titles, column names, and formatting for easy interpretation

Question 21

Bar charts

Answer 21

Discrete, categorical data

Question 22

Pie charts

Answer 22

Represent proportions or relative quantities of values

Should be limited to a small # of clearly labeled categories

Question 23

Histograms

Answer 23

Continuous data divided into discrete categories

Question 23

Proportions

Answer 23

The number of observations with a given characteristic divided by the total number of observations

Often reported as percentages (proportion x 100%)

Question 24

Rates

Answer 24

Computed over a specific time period and use a multiplier

Ex. Per 1000

Examples include mortality and incidence rate

Question 25

Sensitivity

Answer 25

The ability of a test to correctly identify individuals w/ the disease

Proportion of true positives out of all individuals w/ the disease

Question 26

Negative predictive value

Answer 26

Probability an individual does NOT have the disease given a negative test result

Question 26

Specificity

Answer 26

The ability of a test to correctly ID individuals WITHOUT the disease

Proportion of true negatives out of all individuals without the disease

Question 27

Positive predictive value

Answer 27

Probability an individual HAS the diseases given a positive test

Question 28

Receiver operating characteristic (ROC) curves

Answer 28

Illustrate the tradeoff between sensitivity and false positive rate at different decision thresholds

The area under the ROC curve indicates the overall discriminating power of the test