Module 1 - Introduction & Overview

Question 1

Case-Control Studies

Answer 1

• Compares 2 groups of samples with similar characteristics (cases & controls)
• In both groups 1/2 of sample is exposed 1/2 is not
• Researchers compare the differences between each group to determine why the cases got the disease
• Observational Study

Question 2

Categorical Variables

Answer 2

• When values are based on distinct categories of qualities

- Examples: race, gender, religion, etc.

Question 3

What are the 2 broader classifications of variables?

Answer 3

• Types of Variables

- Types of Scales

Question 4

Statistics

Answer 4

Data or a number, the process of analyzing the data

Question 5

A Statistic

Answer 5

A numerical summary of the sample of data

Question 6

Nominal Scale

Answer 6

• Data is grouped into categories
• Examples: Yes/No; normal, overweight, obese
• Categorical Variables

Question 7

Population

Answer 7

Total set of subjects of interest in a study

Question 8

Parameter

Answer 8

A numerical summary of the population based on inferential statistics

Question 9

Quantitative Variables

Answer 9

• The measurement scale has numeric values

- Examples: annual income, age, years of education completed, etc.

Question 10

Inferential Statistics

Answer 10

Predicting information about a population based on data from a sample

Question 11

n=

Answer 11

The total number of subjects in a sample

Question 12

Variables

Answer 12

Characteristics that vary among subjects in a sample or population

Question 13

What are the 2 major categories for study designs?

Answer 13

• Observational

- Experimental

Question 14

Continuous Scale

Answer 14

• Part of Ratio Scale
• Has values on a continuum
• Example: Age

Question 15

Observational Studies

Answer 15

• Observe the variables without intervention

- Example: Study to see if excessive body fat in children is due to a specific gene

Question 16

Ordinal Scale

Answer 16

• Observations are grouped into categories, they are often group
• The difference between each category is not specifically defined
• Example: Ranking subject responses in increasing order, the differences between the adjacent subjects aren’t equal
• Categorical Variables

Question 17

Simple Random Sample

Answer 17

Subjects from a population where each person has an equal chance of being selected

Question 18

Biostatistics

Answer 18

The application of statistics to medicine/health

Question 19

Experimental Studies

Answer 19

-Observe variables with intervention and a control group without intervention to compare the results

Question 20

Ratio Scale

Answer 20

• Scale using numbers, the differences between numbers have meaning on a numerical scale
• AKA Numerical Scale
• Quantitative Variables

Question 21

Randomization

Answer 21

The process of finding a sample that best represents a population

Question 22

Interval Scale

Answer 22

• Questions with numeric answers are summed, which creates a scale
• Example: Satisfaction survey, 0 = not satisfied (rather than no value)
• Quantitative variables

Question 23

Discrete Scale

Answer 23

• Part of Ratio Scale
• Values equal to integers
• Example: Number of injuries

Question 24

What are Steven’s 4 Scales of Measurement

Answer 24

• Ratio Scale
• Interval Scale
• Nominal Scale
• Ordinal Scale
• *Think RINO**

Question 25

Subjects

Answer 25

The entity data is collected from, usually people, but can be families, schools, cities, or companies

Question 26

Cross-Sectional Studies

Answer 26

• Researchers measure the outcome and exposures in the subjects at the same time
• This is commonly used to determine the prevalence of a disease
• Observational Study

Question 27

Sample

Answer 27

A subset of population that data is collected on