Module 1

Question 1

What are the 3 Types of Studies?

Answer 1

1. Qualitative
2. Quantitative
3. Mixed Methods

Question 2

What is Statistics?

Answer 2

“a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data”

Question 3

What is a Variable?

Answer 3

A characteristic that take on different values (measurable or observable) (i.e., it must have variability).

WHAT are you measuring? HOW are you measuring it? WHAT units?

Question 4

What is an Independent Variable (IV) ?
What are other names for the IV?

Answer 4

The variable that is manipulated.
AKA Predictory or Explanatory

Question 5

What is the Dependent Variable (DV)?
What are other names for the DV?

Answer 5

Variable affected by the IV
AKA Criterion, Response or Outcome

Question 6

What is the Scientific Method?

Answer 6

A method of investigation that uses the objective and systematic collection and analysis of empirical data to test theories and hypotheses

Question 7

What is Empirical Data?

Answer 7

Empirical data comes from direct observation or measurement, and it is verifiable

Question 8

What are the 5 Stages of the Scientific Method?

Answer 8

1. Develop a Research Hypothesis to be tested
2. Collect Data
3. Analyze Data
4. Draw a Conclusion related to the Hypothesis
5. Communicate Results

Question 9

What characteristics does a research hypothesis have? (3)

Answer 9

• Identifies the variables
• Identifies the nature and direction of the relationship
• Presents an educated prediction that can be tested

Question 10

Directional vs Non Directional

Answer 10

Question 11

What is a Research Hypothesis?

Answer 11

A statement about the predicted or expected relationship between the variables in the study (mainly words)

Question 12

What is a Statistical Hypothesis?

Answer 12

A statement about the hypothesized population parameters being tested (mainly mathematical symbols)

• Null Hypothesis
• Alternative Hypothesis

Question 13

Differentiate between Research and Statistical Hypotheses.

Answer 13

Statistical hypothesis: Focuses on a specific, measurable statement that can be tested with data.

For example, “The average height of adults in a city is 5’7”.” It’s used in hypothesis testing in statistics to either accept or reject based on data.

Research hypothesis: A broader, theory-driven prediction about relationships between variables.

For example, “The average height of adults in a city is 5’7”.” It’s used in hypothesis testing in statistics to either accept or reject based on data.

For example, “People who exercise regularly have lower stress levels.” It’s formulated before the research begins and is based on theory or previous studies.

Question 14

Directional vs Non-Directional Alternative Hypothesis

Answer 14

Question 15

Differentiate between a Sample and a Population.

Answer 15

A population is the entire group of individuals or items that you want to study or make conclusions about. For example, all adults in a city.

A sample is a subset of the population, selected to represent the population in a study. For example, 100 adults from that city.

Question 16

Why do we need a Sample?

Answer 16

To test hypotheses about the population by collecting data from samples

• More plausible
• Easier
• Cheaper
• Ethically achievable

Question 17

Differentiate between a parameter and a statistic

Answer 17

μ is the population mean (parameter).
x̄ is the sample mean (statistic).

Question 18

What are the 4 Levels of Measurment?

Answer 18

Nominal
Ordinal
Interval
Ratio

Question 19

Nominal

Answer 19

Level, Groups, Categories
Definition: Categorizes data without any order.
Example: Gender, colors, names.
Characteristics: No ranking or numerical meaning.

Question 20

Ordinal

Answer 20

Rankings and Categories

Definition: Categorizes data with a meaningful order, but the intervals between the categories are not consistent or measurable.

Example: Class rankings (1st, 2nd, 3rd), satisfaction ratings (poor, fair, good).

Characteristics: Ordered but differences between ranks are not meaningful.

Question 21

Interval

Answer 21

No absolute zero

Definition: Ordered data with meaningful intervals between values, but no true zero point.

Example: Temperature in Celsius or Fahrenheit, calendar years.

Characteristics: Differences are measurable, but ratios are not meaningful since there’s no absolute zero

Question 22

Ratio

Answer 22

Definition: Like interval, but with a true zero point, allowing for meaningful comparisons of ratios.

Example: Height, weight, age, income.

Characteristics: Both differences and ratios are meaningful due to a true zero.

Question 23

Four levels of meausrement summary

Answer 23

Nominal: Categories without order.
Ordinal: Ordered categories.
Interval: Ordered with measurable intervals but no true zero.
Ratio: Ordered with measurable intervals and a true zero.

Question 24

What are the Two Types of Study Design?

Answer 24

Experimental vs Observational

Question 25

What is an Observational Study?

Answer 25

Only observe, dont interfere
- case control

Question 26

What is an Experimental Study?

Answer 26

measure and make an intervention by changing/introducing a variable

Question 27

What is a Confounding Variable?

Answer 27

A variable that provides an alternative explanation for the relationship between the DV and IV

A variable related to the DV & IV but not located in the causal path.

Question 28

How do we Control for Confounding Variable?

Answer 28

In the study deign:
- Narrow down sample in study - Standardize

Statistical Methods

Question 29

What are the Two objectives of analyzing data?

Answer 29

Summarize the data
- Descriptive Statistics - describe the data

Test hypotheses
- Inferential Statistics
- need both

Question 30

Drawing a Conclusion

Answer 30

Interpret your results within the context of the study/experiment

Ask yourself the following question:
Did your results support your research hypothesis?