Ch 1: Introduction to Statistics

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Ch 1: Introduction to Statistics by Mind Map: Ch 1: Introduction to Statistics

1. Statistical Methods

1.1. Inferential Statistics: uses sample data to make inferences about populations

1.2. Descriptive Statistics: Organizes, summarizes, and simplifies data

2. Statistics: A set of mathematical procedures for organizing, summarizing and interpreting data

2.1. Population: set of all individuals of all interests in a particular study

2.1.1. Parameter - a value, usually numerical, that describes a population

2.1.1.1. Sampling Error: error that exists between a sample statistic and the corresponding population parameter

2.2. Sample: a set of individuals selected from a population

2.2.1. Statistic - a value, usually numerical, that describes a sample

3. Measurements Scales

3.1. Nominal: a set of categories that have different names; label and categorize observations

3.2. Ordinal: set of categories organized in an ordered sequence; rank observations in terms of size or magnitude

3.3. Interval: ordered categories that are all intervals of exactly the same size; no true zero

3.4. Ratio: an interval scale with an absolute zero point

4. Variables: a characteristic or condition that changes or has different values for different individuals

4.1. Discrete Variable: separate indivisible categories

4.2. Continuous Variable: Infinite possible values between any two observed values

4.2.1. Real Limits: boundaries of intervals represented on a continuous number line

4.2.1.1. Upper Real Limits

4.2.1.2. Lower Real Limits

5. Research Methods

5.1. Correlational Method: examines the relationship between two variables but cannot show causation

5.2. Experimental Method: Manipulation of one variable to observe the effects on another variable to show cause-and-effect

5.2.1. Dependent Variable = observed

5.2.2. Independent Variable = manipulated

5.2.3. Control Condition = no treatment

5.2.4. Experimental Condition = treatment

5.3. Non-experimental Method: examine relationships between variables by comparing groups of scores but cannot show causation

6. Scores = X

6.1. X and Y Variables

6.2. n = sample

6.3. N = population

6.4. Σx = summation of all scores