PSYC 243 Exam 1 Study Guide: Statistics

Exam 1 Study Guide: Statistical Analysis & Design (PSYC 243)

• Exam Content: Covers the material from chapters 1-5 of the readings and lectures.
• Question Types: 32 multiple-choice questions (2.5 points each), and 20-point problem set.
• Review Session: A review session will be offered before the exam.
• TA Review Sessions: Undergraduate TAs will also hold review sessions during office hours (listed in the syllabus).
• Required Materials: Pen/pencil, student ID, and an ACT/SAT-approved calculator.

Chapter 1: Introduction to Statistics

• Population: The entire group of interest.
• Sample: A subset of the population.
• Parameter: A numerical description of a population.
• Statistic: A numerical description of a sample.
• Discrete Variables: Variables that can only take on specific values (e.g., whole numbers).
• Continuous Variables: Variables that can take on any value within a given range (e.g., height, weight).
• Nominal Variables: Variables that categorize data into distinct groups (e.g., gender, eye color).
• Ordinal Variables: Variables that categorize and rank data (e.g., education level, satisfaction rating).
• Interval Variables: Variables that categorize, rank and have equal intervals between values (e.g., temperature in Celsius).
• Ratio Variables: Variables that categorize, rank, have equal intervals and possess a true zero point (e.g., height, weight).
• Correlational Studies: Examine the relationship between two or more variables.
• Experimental Studies: Manipulate one or more variables to examine their effect on another.
• Non-Experimental Studies: Observe variables without manipulation to identify relationships.
• Independent Variables: The variable manipulated in a study.
• Dependent Variables: The variable measured in a study.
• Causation: Experimental studies are necessary to determine causality.

Chapter 2: Frequency Distributions

• Frequency Tables: Tables that summarize the frequency of data values.
• Bar Graphs: Graphs that display categorical data.
• Histograms: Graphs that display continuous data, with bars touching.
• Polygons: Graphs that connect points representing frequencies, sometimes used with histograms.
• Normal Curve: A bell-shaped curve, often observed in natural phenomena.
• Stem-and-Leaf Plots: Data visualization method for ordered data.
• Central Tendency Measures of central tendency are the value at the centre of the data. Mean, Median and Mode are examples.

Chapter 3: Central Tendency

• Mean: The average of the data.
• Median: The middle value in a sorted dataset.
• Mode: The most frequent value.
• Symmetrical Distributions: Mean, median, and mode are equal.
• Skewed Distributions: Mean, median, and mode not equal, skewed to the direction of outlier data.
• Positive Skew: The tail of the distribution extends to the right.
• Negative Skew: The tail of the distribution extends to the left.

Chapter 4: Variability

• Sum of Squares: A calculation in statistics to measure the spread of data.
• Variance: A measure of how spread out the data is.
• Standard Deviation: A measure of the dispersion of a dataset relative to its mean.
• Range: Distance between the highest and lowest values in a dataset.

Chapter 5: Z-Scores

• Z-score: A standardized score that shows the distance of a data point from the mean in terms of standard deviations.
• Z-score Interpretation: Expresses how many standard deviations a score is above or below the mean. A z-score of zero means the score is equal to the mean. A positive z-score means the score is above the mean and a negative z-score means the score is below the mean.