Introduction to Statistics

Experimental Method

Allows a cause-and-effect explanation; IV is manipulated, and DV is observed/measured.

Non-Experimental Method

Does not allow a cause-and-effect explanation; IV and DV are observed/measured.

Non-Experimental Method IV

Quasi IV

nEM Types

Correlational Research; Non-Equivalent Groups; Pre-Post studies.

Variable Types

Discrete or Continuous

Discrete Variable

Separate and countable categories, e.g., blood type or no. of children.

Continuous Variable

Infinity between two values, e.g., age, distance, or speed.

Scales of Measurement (Measuring Variables)

Categorical or Metric

Categorical

Nominal or Ordinal

Metric

Interval or Ratio

Nominal

labels/names the group, e.g., Gender.

Ordinal

Labels and orders, e.g., Chapters. 

Interval

Labels and orders, and intervals are equal, e.g., Temperature.

Ratio

Labels and orders, and intervals are equal and zero, e.g., No. of Correct Answers on Test.

N

Population

n

Sample

X

Raw scores; originals from data collection

Σ

Sigma; Summation; Total

Order of Operations

Brackets; Squaring; Multiplication and Division (if multiple: L —> R); Summation; Subtracting.

Bias

Any effect that renders the result non-representative

Bias Types

Selection Bias and Information Bias

Selection Bias

Sample (n) does not represent population (N)

Information Bias

Issues re: information collection/measurement

Information Bias Types

Emotive language; Leading question; Double-barrelled question; Unclear question. 

Identifying Bias

• How were the individuals / objects in the study selected?

• What measurements were made / what questions were asked?

• Who conducted / sponsored the study?

Avoiding Bias

Random Sampling; Non-leading Language; Reliable/Credible Source

Why avoid bias?

Because it negates meaningful conclusions being drawn about the population of interest, which is the whole point of research!