Statistics Exam 1 Study Guide

Questions and Answers

What is a key distinction between a population and a sample?

A population includes a selected set of individuals.

A sample includes all possible members of the group.

A population encompasses all individuals of a specific group. (correct)

A parameter describes a sample while a statistic describes a population.

Which of the following describes a positively skewed distribution?

It has a tail on the left with many higher values.

It is uniformly distributed across all values.

It has a tail on the right with a few much higher values. (correct)

It has a balanced distribution with a center peak.

What accurately distinguishes an independent variable from a dependent variable?

Independent variables are outcomes measured in a study.

Dependent variables depend on the variation of independent variables. (correct)

Independent variables are those whose effects are measured.

Dependent variables are manipulated or categorized.

Which level of measurement is characterized by equal intervals and a true zero?

<p>Ratio</p> Signup and view all the answers

Which statement correctly reflects the relationship between correlation and causation?

<p>Correlation can occur without causation being present.</p> Signup and view all the answers

Study Notes

Population vs. Sample

Population: Comprises all members of a group targeted for study.
Sample: A subset of individuals selected from a population to represent it.
Parameter: Describes characteristics of a population.
Statistic: Describes characteristics of a sample.

Independent and Dependent Variables

Independent Variable: The manipulated or classified variable in an experiment (example needed).
Dependent Variable: The outcome or effect that is measured (example needed).

Types of Variables

Discrete Variables: Take specific values; for example, counting items like the number of squirrels.
Continuous Variables: Can take any value within a given range; examples include measurements like height or temperature.

Levels of Measurement

Nominal: Categorical data without a specific order (qualitative).
Ordinal: Categorical data with a meaningful order, but intervals are not equal (qualitative).
Interval: Numeric data with equal intervals but no true zero (quantitative).
Ratio: Numeric data with equal intervals and a true zero point (quantitative).

Understanding Skewed Distributions

Positive Skew: Characterized by a tail on the right, indicating a few high values (e.g., tall people).
Negative Skew: Characterized by a tail on the left, indicating a few low values (e.g., short people).

Research Study Designs

Correlational Studies: Examine the relationship between two different variables without manipulation; data is observed and collected.
Experimental Studies: Involve the manipulation of independent variables to assess their effects on dependent variables.

Summation Notation (Σ)

Σ Notation: Represents the sum of a series of values, such as ΣX, which indicates the total of all X values.
Note: Understanding from here is less critical.

Correlation vs. Causation

Correlation: Refers to a relationship between two variables, but does not indicate that one causes the other.

Description

This study guide covers key concepts for the first exam in statistics, focusing on the differences between population and sample, as well as independent and dependent variables. It provides a clear understanding of how researchers define and use these concepts when conducting studies.