Statistics Quiz: Key Concepts and Measures
56 Questions
2 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to Lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

Which statistical measure is least affected by extreme values in a data set?

  • Mode
  • Median (correct)
  • Range
  • Mean

In a normal distribution, what does the bell curve signify about the relationship between the mean, median, and mode?

  • Mean, median, and mode are all equal (correct)
  • Mean is greater than the median and mode
  • Median is greater than mean and mode
  • Mode is significantly lower than mean and median

Which of the following is a key characteristic of inferential statistics?

  • Infers relationships between variables from sample data (correct)
  • Calculates frequencies and percentages
  • Only uses graphical representations of data
  • Describes the dataset without making predictions

What might be a potential pitfall in statistical reporting?

<p>Failing to report sample sizes (B)</p> Signup and view all the answers

Which of the following is a method of measuring spread in descriptive statistics?

<p>Standard Deviation (B)</p> Signup and view all the answers

What is the primary purpose of using statistical analyses in research?

<p>To objectively summarize or infer from a set of data (C)</p> Signup and view all the answers

Which average is computed as the sum of scores divided by the number of scores?

<p>Mean (A)</p> Signup and view all the answers

What does a high variance indicate about a dataset?

<p>Data points vary widely from the mean (C)</p> Signup and view all the answers

What measure of spread corresponds with the median in a distribution?

<p>Interquartile range (D)</p> Signup and view all the answers

Which type of inferential statistic is primarily used to analyze the relationship between two continuous variables?

<p>Pearson correlation coefficient (B)</p> Signup and view all the answers

Which of the following visual representations is best suited for displaying the median and interquartile range of a dataset?

<p>Box plot (B)</p> Signup and view all the answers

In a negatively skewed distribution, which average value is typically greater than the others?

<p>Mode (C)</p> Signup and view all the answers

Which graph is NOT typically used for descriptive statistics?

<p>Line chart (A)</p> Signup and view all the answers

Which of the following hypotheses is an example of a proposed relation between variables?

<p>The temperature affects the amount of ice cream sold. (C)</p> Signup and view all the answers

Which measure of spread has no corresponding average value associated with it?

<p>Mode (C)</p> Signup and view all the answers

In which situation would a Mann-Whitney U test be most appropriately used?

<p>Analyzing the differences between two independent groups without normality (A)</p> Signup and view all the answers

What does Pearson’s Coefficient of Correlation (r) specifically measure?

<p>Covariance standardized by the product of standard deviations (A)</p> Signup and view all the answers

Which of the following correctly describes Spearman’s Coefficient of Rank Correlation (ρ)?

<p>Computes the covariance of ranks (A)</p> Signup and view all the answers

In a correlation analysis, what does the 'degrees of freedom' refer to?

<p>The number of observations minus two (C)</p> Signup and view all the answers

Which of the following measures represents the proportion of variance explained by a correlation?

<p>Variance explained (R2) (B)</p> Signup and view all the answers

Which of the following statements about correlations is true?

<p>Correlations reveal the relationship between two variables. (C)</p> Signup and view all the answers

What does a correlation coefficient of r(168) = -.43, p < .05 indicate?

<p>The correlation is statistically significant. (D)</p> Signup and view all the answers

What is the main limitation of correlational designs?

<p>They do not provide information about differences between groups. (D)</p> Signup and view all the answers

Which of the following measures is not standardized?

<p>Covariance (C)</p> Signup and view all the answers

What does a regression analysis primarily examine?

<p>How two or more variables are related (B)</p> Signup and view all the answers

In the equation of regression $y = ax + b$, what does the term 'a' represent?

<p>The change in y for every unit increase in x (C)</p> Signup and view all the answers

What is a key aspect that correlation coefficients do not indicate?

<p>If one variable causes the other (A)</p> Signup and view all the answers

Which test can be used to determine if two correlation coefficients are different?

<p>Fisher Z test (D)</p> Signup and view all the answers

In a within-subjects design, how is the independent variable presented?

<p>All participants experience both conditions (C)</p> Signup and view all the answers

What does the p-value in a statistical test represent?

<p>The likelihood of observing the data if the null hypothesis is true (B)</p> Signup and view all the answers

When there are two predictors in a regression model, what does the regression equation represent?

<p>A plane of best fit (B)</p> Signup and view all the answers

What is a key feature of the matched-subjects experimental design?

<p>Participants are paired based on specific characteristics (D)</p> Signup and view all the answers

In what scenario is a between-subjects design primarily used?

<p>When comparing two different treatment conditions (B)</p> Signup and view all the answers

What type of questions will be included in Test 3?

<p>Both factual and applied questions (A)</p> Signup and view all the answers

Which lecture topics are suggested for special attention in preparation for upcoming tests?

<p>Lectures 2, 9, 10, and 11 (C)</p> Signup and view all the answers

What is the focus of Lecture 12 in Semester 2?

<p>Probability and Distributions (C)</p> Signup and view all the answers

When is the deadline for the Coursework Assignment?

<p>April 25 (D)</p> Signup and view all the answers

What type of test is scheduled for March 28?

<p>In-Class Test (C)</p> Signup and view all the answers

What will be the primary content of the lectures after the mid-term exams?

<p>ANOVA tests and their applications (D)</p> Signup and view all the answers

What is the purpose of the resit opportunity offered on May 2?

<p>To take class tests only for those with exceptional circumstances (D)</p> Signup and view all the answers

In which lecture will Non-Parametric Tests be covered?

<p>Lectures 15 and 16 (A)</p> Signup and view all the answers

What is the main purpose of the null hypothesis in statistical testing?

<p>To state that there is no difference between groups (D)</p> Signup and view all the answers

When using a paired-samples t-test, which condition is being measured?

<p>Differences within the same group at different times (B)</p> Signup and view all the answers

What does a Type I Error in hypothesis testing represent?

<p>Rejecting the null hypothesis when it is true (D)</p> Signup and view all the answers

Which of the following factors can increase the probability of obtaining a Type II Error?

<p>A confounding variable that affects results (B), A smaller effect size between groups (D)</p> Signup and view all the answers

What is the role of counter-balancing in within-subjects designs?

<p>To ensure that the order of treatment does not confound results (C)</p> Signup and view all the answers

How is the significance level (alpha) typically determined in hypothesis testing?

<p>It is a predetermined threshold indicating the probability of a Type I Error (C)</p> Signup and view all the answers

What do inferential statistics primarily test?

<p>The validity of the null and alternative hypotheses (B)</p> Signup and view all the answers

Which of the following statements about the Student t-tests is true?

<p>One-sample t-tests compare a single group against a known value (D)</p> Signup and view all the answers

What does it indicate if a result has a p-value of 0.01?

<p>The evidence against the null hypothesis is strong (C)</p> Signup and view all the answers

What is the consequence of incorrectly rejecting the null hypothesis?

<p>It leads to a Type I Error (A)</p> Signup and view all the answers

Which statistical test would be appropriate if there are more than two groups being compared?

<p>Analysis of Variance (ANOVA) (D)</p> Signup and view all the answers

What are the implications if a hypothesis test suggests a significant difference when there are confounding variables?

<p>The results may be misleading and incorrect (C)</p> Signup and view all the answers

Which of the following is NOT a factor affecting the probability 'p' in hypothesis testing?

<p>The correlation between variables (D)</p> Signup and view all the answers

What is meant by causality in the context of experimental designs?

<p>It suggests a direct cause-and-effect relationship between variables (A)</p> Signup and view all the answers

What does the alternative hypothesis indicate in hypothesis testing?

<p>That at least one significant difference exists (D)</p> Signup and view all the answers

Flashcards

Descriptive Statistics

Statistical methods that help summarize and describe data sets. Examples include mean, median, mode, range, and standard deviation.

Mode

The most frequent score or scores in a data set.

Median

The middle value of a data set when all scores are arranged in order.

Mean

The sum of all scores divided by the total number of scores, often used to represent the average of a data set.

Signup and view all the flashcards

Normal Distribution

A bell-shaped curve distribution where the mean, median, and mode are equal. This is a common distribution in data analysis.

Signup and view all the flashcards

Inferential Statistics

Statistical methods that help determine if there is a relationship between two or more variables using data analysis. Example: analyzing if there is a correlation between hours of study and exam scores.

Signup and view all the flashcards

Measures of Spread

The spread or variability of data around the average. Examples include range, standard deviation, and variance.

Signup and view all the flashcards

Variance

A type of descriptive statistics which quantifies the spread of data around the mean. It is a measure of how much the data points deviate from the average, and its square root is the standard deviation.

Signup and view all the flashcards

Skewed Distribution

A type of data distribution where the values are clustered around the mean, but there is a tail extending to one side, making it asymmetrical.

Signup and view all the flashcards

Positively Skewed Distribution

A type of skewed distribution where the tail extends towards higher values.

Signup and view all the flashcards

Negatively Skewed Distribution

A type of skewed distribution where the tail extends towards lower values.

Signup and view all the flashcards

Range

A type of descriptive statistic showing the distance between the highest and lowest values in a data set.

Signup and view all the flashcards

Interquartile Range (IQR)

A type of descriptive statistic representing the difference between the third and first quartiles in a data set. It measures the middle 50% of the data distribution.

Signup and view all the flashcards

Histogram

A visual representation of data distribution using bars to indicate the frequency of each value.

Signup and view all the flashcards

Population Pyramid

A visual representation of two groups of data using bars to compare their frequencies. Often used to represent population demographics.

Signup and view all the flashcards

Correlation

A statistical measure that examines the relationship between two variables.

Signup and view all the flashcards

Correlation Coefficient (r)

A correlation coefficient represents the strength and direction of a relationship between two variables.

Signup and view all the flashcards

Variance Explained (R^2)

A measure of the variability in a data set, indicating how spread out the data points are around the mean.

Signup and view all the flashcards

Spearman’s Coefficient of Rank Correlation (rho)

A statistical measure that examines the association between two variables, but for ordinal data.

Signup and view all the flashcards

Degrees of Freedom

The number of independent observations used in a correlation analysis, indicating how many data points were considered.

Signup and view all the flashcards

Direction of Correlation

The direction of a correlation, indicated by a positive or negative sign in the correlation coefficient.

Signup and view all the flashcards

Significance Test (p-value)

A statistical test conducted to examine whether a correlation is statistically significant, meaning it's unlikely to have occurred by chance.

Signup and view all the flashcards

Number of Observations (N)

The number of observations or data points used in a correlation analysis, denoted by 'N'.

Signup and view all the flashcards

Magnitude of Correlation

The strength of a correlation between two variables, measured by a correlation coefficient. A value closer to 1 indicates a stronger relation.

Signup and view all the flashcards

p-value of correlation

The statistical significance of a correlation, indicating the likelihood that the relationship is just due to chance.

Signup and view all the flashcards

Fisher Z Test

A statistical test used to examine whether two correlation coefficients significantly differ from each other

Signup and view all the flashcards

Regression Analysis

A statistical technique used to determine the relationship between two variables, or how much a dependent variable changes in response to a change in one or more independent variables.

Signup and view all the flashcards

Predictor Variable

The variable that is controlled or manipulated in a regression analysis, used to predict the dependent variable.

Signup and view all the flashcards

Criterion Variable

The variable that is being predicted or measured in a regression analysis.

Signup and view all the flashcards

Between-Subjects Design

A statistical technique where each participant receives a treatment or condition, and the results are compared across groups. e.g., independent-samples t-test.

Signup and view all the flashcards

Within-Subjects Design

A statistical technique where all participants are exposed to all treatments or conditions. e.g., paired-samples t-test.

Signup and view all the flashcards

Significance Testing

A statistical test to determine the likelihood that the observed results occurred by chance.

Signup and view all the flashcards

Null Hypothesis (H0)

A statement that there is no difference or relationship between variables. It's the starting point for statistical testing.

Signup and view all the flashcards

Alternative Hypothesis (H1)

A statement that suggests a difference or relationship between variables. It's what researchers want to support.

Signup and view all the flashcards

Student's T-Test

A statistical test used to determine if there is a significant difference between two groups or conditions when the independent variable has two levels.

Signup and view all the flashcards

Independent Samples T-test

A type of t-test used when comparing two groups that are independent of each other (e.g., treatment group vs. control group).

Signup and view all the flashcards

Paired Samples T-test

A type of t-test used when comparing two conditions experienced by the same group (e.g., before and after treatment).

Signup and view all the flashcards

Probability (p)

The probability that the observed difference between groups is due to chance alone, assuming the null hypothesis is true.

Signup and view all the flashcards

Alpha Level (α)

The threshold for determining statistical significance. If the probability (p) is less than the alpha, the null hypothesis is rejected.

Signup and view all the flashcards

Type I Error

A type of error that occurs when the null hypothesis is incorrectly rejected, leading to a false positive conclusion.

Signup and view all the flashcards

Type II Error

A type of error that occurs when the null hypothesis is incorrectly accepted, leading to a false negative conclusion.

Signup and view all the flashcards

Bayesian Statistics

A statistical approach that focuses on the probability of the data given a hypothesis, rather than the probability of the hypothesis given the data.

Signup and view all the flashcards

Confounding Variables

Factors that influence the likelihood of a Type I error. They can make a difference appear significant when it is not.

Signup and view all the flashcards

Extraneous Variables

Factors that influence the likelihood of a Type II error. They can make a real difference harder to detect.

Signup and view all the flashcards

Interpretation of Statistical Results

The outcome of statistical analyses should only be interpreted in relation to the specific study conducted. It doesn't provide absolute proof.

Signup and view all the flashcards

Study Notes

Course Information

  • Course Title: PSGY1014 - Research Methods and Analyses 1
  • Revision Semester: 1
  • Instructor: Prof Steve Janssen
  • Date: February 1, 2024

Module Objectives

  • Understand the process of scientific discovery
  • Identify differences between effects and noise
  • Recognize common pitfalls in statistical reporting
  • Know how to apply common statistical tests (SPSS or JASP)
  • Interpret and report test results

Why Statistics?

  • Statistical analyses help researchers:
    • Describe data (descriptive statistics)
    • Determine relationships between variables (inferential statistics)

Descriptive Statistics

  • Frequencies (numbers, percentages, proportions)
  • Averages (mean, median, mode)
  • Measures of spread:
    • Range (min, max)
    • Interquartile range (Q3-Q1)
    • Variance
    • Standard deviation
    • Standard error

Averages

  • Mode: Most frequent score
  • Median: Middle score (ranked)
  • Mean: Sum of scores divided by total scores

Normal Distribution

  • Shaped like a bell curve
  • Mean, median, and mode have the same value

Skewed Distributions

  • Mean, median, and mode differ
  • Positively skewed: tail extends to the right
  • Negatively skewed: tail extends to the left
  • Skewness affects choice of inferential statistics

Measures of Spread

  • Related to averages
  • Median: Range, interquartile range
  • Mean: Variance, standard deviation, population estimated standard deviation, standard error
  • Mode: No corresponding measure of spread

Exploring Data with Graphs

  • Descriptive: Stem-and-leaf plots, histograms, population pyramids
  • Inferential: Bar charts (means and standard errors), line charts (means and standard errors), boxplots (median and interquartile range), scatter plots (for correlational designs)

Graphs Described

  • Stem-and-Leaf Plots
  • Histograms: Excuses for being late to class
  • Population Pyramids: World population 2019
  • Bar Charts (e.g., example provided)
  • Line Charts: Wildlife population over time
  • Box Plots: Exam scores for 2 classes.
  • Scatter Plots: Height vs weight

Inferential Statistics

  • Student t-tests
  • Correlation coefficients (Pearson & Spearman)
  • Regression analyses
  • Chi-square tests
  • Mann-Whitney, Wilcoxon, Kruskal-Wallis, Friedman
  • Analyses of variance (ANOVA)
  • Used to examine relationships between variables

Hypotheses

  • Formal statements of proposed relationships
  • Null hypothesis (H₀): No effect or relationship
  • Alternative hypothesis (H₁): There is an effect or relationship

Variables

  • Independent variable: Manipulated variable
    • Time spent learning
  • Dependent variable: Measured outcome variable
    • Exam grade
  • Confounding variable: Unequally distributed among conditions
  • Extraneous (nuisance) variable: Equally distributed among conditions
  • The independent variable can be manipulated or varied.

Measurement Scales

  • Nominal: Categories without order (e.g., gender, ethnicity)
  • Ordinal: Categories with order (e.g., military rank, educational levels)
  • Interval: Equal intervals between values (e.g., IQ scores, some questionnaires)
  • Ratio: Interval scale with a true zero point (e.g., age, reaction time)

Parametric vs. Non-Parametric Tests

  • Parametric tests (t-tests, ANOVAs): Require interval or ratio data and normal distribution,
  • Non-parametric tests: Use nominal or ordinal data or when data distribution is abnormal.

Experimental Designs

  • Correlational: No manipulation of variables, only examine relationships.
  • Experimental: Independent variable is manipulated to establish causality.
  • Quasi-experimental: Independent variable cannot be manipulated directly (e.g., comparing groups already formed in reality)

### Additional Pages

  • Socrative details for class interaction
  • Semester 2 schedule and important dates
  • Different types of tests and analysis
  • Importance of considering potential confounding and extraneous variables when interpreting experimental designs
  • The importance of properly formulated hypotheses.
  • Concepts covered in the course: types of errors, significance levels, and how to interpret the results of statistical analysis.
  • Information on Correlations (definitions, components of a correlation coefficient, interpretation, and its use).
  • Regression: how to interpret regression lines along with the description of coefficients
  • Probability: How to interpret and work with p-value
  • Significance: what is meant by significance and type I and II errors
  • Degrees of freedom: and how to calculate
  • Direction: positive and negative correlations, its effects and interpretation.
  • Magnitude: how to interpret correlation magnitudes
  • How to use various graphs: such as bar plots, box plots to depict different analyses

Test Preparation

  • Pay close attention to Lectures 2, 9, 10, and 11

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Quiz Team

Related Documents

PSGY1014 Research Methods and Analyses 1 Revision Semester 1 PDF

Description

Test your understanding of key statistical concepts and measures with this quiz. It covers topics such as measures of central tendency, inferential statistics, and the characteristics of distributions. Perfect for students seeking to reinforce their knowledge in statistics.

More Like This

Use Quizgecko on...
Browser
Open
Browser
Browser