Data Analysis Lecture 5: Correlation

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

What is a correlation?

  • A relationship between two or more variables
  • A relationship between a variable and a constant
  • A relationship between two variables (correct)
  • A relationship between two or more constants

What type of correlation is present when an increase in one variable leads to an increase in another?

  • Zero correlation
  • Positive correlation (correct)
  • Partial correlation
  • Negative correlation

Which correlation coefficient is calculated using the 'Analyze -> Correlate -> Bivariate' option in SPSS?

  • Point-biserial
  • Spearman's rho
  • Pearson's r (correct)
  • Kendall's tau

What is the range of values for Pearson's r?

<p>-1 to 1 (C)</p> Signup and view all the answers

What is the difference between a one-tailed and a two-tailed hypothesis?

<p>One-tailed tests are used for directional hypotheses, while two-tailed tests are used for non-directional hypotheses. (A)</p> Signup and view all the answers

What does a negative t-value indicate in the context of this analysis?

<p>The mean of the real condition was higher than the mean of the picture condition. (C)</p> Signup and view all the answers

In the output of the independent samples t-test, which row should be interpreted when the Levene's test results are non-significant?

<p>Equality of variances assumed (D)</p> Signup and view all the answers

What statistical test is used to determine if there is a significant difference between the means of two groups?

<p>Independent samples t-test (A)</p> Signup and view all the answers

What does 't(11) = -2.47, p = .031' indicate in the context of this analysis?

<p>There is a significant difference in anxiety levels between the real spider and picture conditions, with real spider exposure leading to higher anxiety. (C)</p> Signup and view all the answers

What is the purpose of defining the groups in SPSS for the independent samples t-test?

<p>To tell SPSS which values correspond to each of the two conditions in the data. (D)</p> Signup and view all the answers

What is the name of the SPSS procedure used to perform a dependent t-test?

<p>Analyze -&gt; Compare means -&gt; Paired Samples T Test (C)</p> Signup and view all the answers

In the output of a dependent t-test, what does the 'Paired Samples Statistics' table display?

<p>The mean, standard deviation, and number of participants for each condition (D)</p> Signup and view all the answers

Why is correlation not a significant concern in a dependent t-test?

<p>Because the same participants are used in both conditions, making the scores dependent. (D)</p> Signup and view all the answers

The output of a dependent t-test also includes a 'Paired Samples Correlations' table. What information does this table provide?

<p>The strength of the correlation between the two conditions (B)</p> Signup and view all the answers

What does the 'Paired Samples T-Test' table in the output tell us?

<p>Whether there is a significant difference between the means of the two conditions (B)</p> Signup and view all the answers

What is the primary difference between a dependent t-test and an independent t-test?

<p>A dependent t-test uses the same group of participants exposed to two different conditions, while an independent t-test uses two different groups of participants. (C)</p> Signup and view all the answers

What does the assumption of homogeneity of variance refer to in the context of independent t-tests?

<p>The variances of the two groups being compared should be equal. (B)</p> Signup and view all the answers

Which assumption is relevant for both independent and dependent t-tests?

<p>Normally distributed data. (A)</p> Signup and view all the answers

What is the major purpose of a t-test?

<p>To compare the means of two groups or conditions. (B)</p> Signup and view all the answers

What does it mean when a t-test result is considered "statistically significant"?

<p>The difference between the means is large enough to be unlikely due to chance alone. (A)</p> Signup and view all the answers

Why is the assumption of independence of scores crucial for t-tests?

<p>To avoid confounding effects from participants appearing in multiple groups. (C)</p> Signup and view all the answers

Which of the following is NOT an assumption of t-tests?

<p>The groups being compared should have equal sample sizes. (A)</p> Signup and view all the answers

Flashcards

Correlation

A relationship between two variables, showing how one may affect the other.

Positive correlation

When one variable increases, the other variable also increases.

Pearson's r

A measure of the linear correlation between two variables, ranging from -1 to 1.

Negative correlation

When one variable increases, the other variable decreases.

Signup and view all the flashcards

Significance level (p-value)

Indicates the probability that a correlation is due to chance, with p < .05 considered significant.

Signup and view all the flashcards

Signup and view all the flashcards

Dependent t-test

A statistical test comparing two related groups to determine if their means differ significantly.

Signup and view all the flashcards

Paired samples statistics

Table showing means, sample sizes, and standard deviations for each condition in a dependent t-test.

Signup and view all the flashcards

Correlation in dependent t-test

The relationship of scores in paired conditions, indicating expected dependence among them.

Signup and view all the flashcards

Paired samples t-test table

Output that indicates if the mean difference between two conditions is statistically significant.

Signup and view all the flashcards

Confidence intervals in t-test

Range within which the true population mean difference is likely to fall.

Signup and view all the flashcards

T-test

A statistical test comparing means of two groups.

Signup and view all the flashcards

Normal distribution

A symmetrical bell-shaped frequency distribution of data.

Signup and view all the flashcards

Homogeneity of variance

Assumption that variances are the same across groups.

Signup and view all the flashcards

Independence of scores

Assumption that scores in groups do not influence each other.

Signup and view all the flashcards

Means comparison

The process of comparing average values between groups.

Signup and view all the flashcards

Significant difference

A difference in means that is unlikely due to chance.

Signup and view all the flashcards

Error Mean

The average difference from standard values based on degrees of freedom (df).

Signup and view all the flashcards

t-test Significance (p-value)

A statistical measure indicating if results are significant; p < .05 is significant.

Signup and view all the flashcards

Independent Samples t-test

A test comparing means from two different groups to see if they are significantly different.

Signup and view all the flashcards

Group Statistics Table

Table displaying counts (N), means, standard deviations, and standard error for each condition in a t-test.

Signup and view all the flashcards

Levene’s Test

A test to check if variances are equal between groups in a t-test analysis.

Signup and view all the flashcards

Study Notes

Data Analysis Lecture 5: Correlation

  • Correlation measures the relationship between two variables.
  • Positive correlation: one variable increases as the other increases.
  • Negative correlation: one variable increases as the other decreases.
  • Correlation coefficients range from -1 (perfect negative) to +1 (perfect positive), with 0 indicating no relationship.
  • Types of correlations include Pearson's r, Spearman's rho, Kendall's tau, point-biserial, and partial correlations.
  • Different correlation types are used depending on the data characteristics.

Types of Correlation Coefficients

  • Pearson's r: Used with interval/ratio data and assumes a linear relationship.
  • Spearman's rho: Used with ordinal data, ranks variables, and is not sensitive to outliers.
  • Kendall's tau: Another correlation measure for ordinal data; less sensitive to outliers than Spearman's rho.

Correlation and SPSS

  • SPSS is used to evaluate whether the relationship between variables is significant .
  • Analyze -> Correlate -> Bivariate.
  • Datasets such as Exam Anxiety can be used to analyze correlations.

Pearson's r

  • Values between -1 and +1.
  • p value less than .05, or .01, or .001 indicates statistical significance.
  • SPSS outputs correlations, significance values, and sample size (N).
  • Exam performance negatively correlates with exam anxiety (r=-.44, p<.01).
  • Exam performance positively correlates with time spent revising (r=.40, p<.01).
  • Time spent revising negatively correlates with exam anxiety (r=-.71, p<.01).

Assumptions of Pearson's r

  • Interval or ratio level data.
  • Normally distributed data.
  • Parametric test.

Difference between Parametric and Non-parametric Tests

  • Parametric tests rely on underlying population parameters.
  • Non-parametric tests do not assume anything about the distribution.

Spearman's rho

  • Used when data are ordinal, like ranks.
  • Data set example is 'The Biggest Liar' competition.
  • Creativity level negatively correlates with position (r_s = -.37, p<.01).

Kendall's tau

  • Another ordinal correlation measure.
  • Creativity negatively correlates with position in 'The Biggest Liar' competition (Ï„ = -.30, p < .01).
  • Kendall's Ï„ is often used when there are a lot of tied ranks.

Biserial and Point-Biserial Correlations

  • Used when one variable is dichotomous (e.g., gender).
  • Dichotomous means there are only two categories (e.g., male/female).
  • Biserial correlation assumes an underlying continuum (e.g., prettiness).
  • Point-biserial correlation does not assume an underlying continuum (e.g., pregnancy).

Point-biserial correlations

  • Example dataset: PBCorr
  • Gender of cat is related to time spent away from home (r_pb = .38, p < .01).

Partial Correlations

  • Controls for the effect of a third variable on a relationship.
  • Used to examine the relationship between two variables when a third variable is influencing either (or both).
  • Example: Relationship between exam performance and exam anxiety controlling for time spent revising.
  • In the example, the correlation between exam performance and exam anxiety is reduced from -.44 to -.247 when controlling for the revision time variable.
  • SPSS output shows the correlation matrix of zero-order correlations first, then a matrix of correlations for the variables controlling for a third.

Studying That Suits You

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

Quiz Team

Related Documents

T-Test Lecture 6 PDF

More Like This

KoreliacinÄ— analizÄ— ir statistika
9 questions
Quantitative Analytical Methods Quiz
13 questions
Quantitative Data Analysis Quiz
10 questions
Use Quizgecko on...
Browser
Browser