Module 1 Flashcards

1
Q

What are the 3 Types of Studies?

A
  1. Qualitative
  2. Quantitative
  3. Mixed Methods
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2
Q

What is Statistics?

A

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

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3
Q

What is a Variable?

A

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?

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4
Q

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

A

The variable that is manipulated.
AKA Predictory or Explanatory

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5
Q

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

A

Variable affected by the IV
AKA Criterion, Response or Outcome

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6
Q

What is the Scientific Method?

A

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

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7
Q

What is Empirical Data?

A

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

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8
Q

What are the 5 Stages of the Scientific Method?

A
  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
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9
Q

What characteristics does a research hypothesis have? (3)

A
  • Identifies the variables
  • Identifies the nature and direction of the relationship
  • Presents an educated prediction that can be tested
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10
Q

Directional vs Non Directional

A
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11
Q

What is a Research Hypothesis?

A

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

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12
Q

What is a Statistical Hypothesis?

A

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

  • Null Hypothesis
  • Alternative Hypothesis
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13
Q

Differentiate between Research and Statistical Hypotheses.

A

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.

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14
Q

Directional vs Non-Directional Alternative Hypothesis

A
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15
Q

Differentiate between a Sample and a Population.

A

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.

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16
Q

Why do we need a Sample?

A

To test hypotheses about the population by collecting data from samples

  • More plausible
  • Easier
  • Cheaper
  • Ethically achievable
17
Q

Differentiate between a parameter and a statistic

A

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

18
Q

What are the 4 Levels of Measurment?

A

Nominal
Ordinal
Interval
Ratio

19
Q

Nominal

A

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

20
Q

Ordinal

A

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.

21
Q

Interval

A

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

22
Q

Ratio

A

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.

23
Q

Four levels of meausrement summary

A

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.

24
Q

What are the Two Types of Study Design?

A

Experimental vs Observational

25
Q

What is an Observational Study?

A

Only observe, dont interfere
- case control

26
Q

What is an Experimental Study?

A

measure and make an intervention by changing/introducing a variable

27
Q

What is a Confounding Variable?

A

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.

28
Q

How do we Control for Confounding Variable?

A

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

Statistical Methods

29
Q

What are the Two objectives of analyzing data?

A

Summarize the data
- Descriptive Statistics - describe the data

Test hypotheses
- Inferential Statistics
- need both

30
Q

Drawing a Conclusion

A

Interpret your results within the context of the study/experiment

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