Data Analysis Lecture 3 & 4

<p>There is a significant link between the variables. (C)</p> Signup and view all the answers

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

<p>The null hypothesis is accepted, indicating no significant differences exist. (D)</p> Signup and view all the answers

<p>The pre-task planning group produced significantly more syllables than the no planning group. (B)</p> Signup and view all the answers

<p>5 to 10 (D)</p> Signup and view all the answers

<p>Bartlett's test of sphericity (C)</p> Signup and view all the answers

<p>To reduce a large number of items into smaller dimensions for simpler analysis. (D)</p> Signup and view all the answers

<p>High reliability (B)</p> Signup and view all the answers

<p>No significant differences were found between the two groups. (D)</p> Signup and view all the answers

<p>Eigenvalue greater than 1 (A)</p> Signup and view all the answers

<p>There are significant differences in the mean scores. (C)</p> Signup and view all the answers

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

<p>69.6 (D)</p> Signup and view all the answers

<p>16.44342 (D)</p> Signup and view all the answers

<p>Use Z scores (C)</p> Signup and view all the answers

<p>Strong negative correlation (C)</p> Signup and view all the answers

<p>0.01 (C)</p> Signup and view all the answers

<p>The standard deviation relative to the mean (C)</p> Signup and view all the answers

<p>Assessing the relationship between two continuous variables (A)</p> Signup and view all the answers

<p>It visually displays outliers and the distribution of the dataset. (A)</p> Signup and view all the answers

<p>0.05 (C)</p> Signup and view all the answers

<p>r = 1 (D)</p> Signup and view all the answers

<p>Variables are measured on an ordinal scale (B)</p> Signup and view all the answers

<p>Monotonic relationship (B)</p> Signup and view all the answers

<p>Reject H0 (A)</p> Signup and view all the answers

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

<p>Skewness and kurtosis should be between -1 and 1 (B)</p> Signup and view all the answers

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

<p>0.387 (C)</p> Signup and view all the answers

<p>It must be measured at interval-ratio level. (C)</p> Signup and view all the answers

<p>p &lt; 0.05 (D)</p> Signup and view all the answers

<p>If variances are not equal. (D)</p> Signup and view all the answers

<p>The groups do not have equal variances. (D)</p> Signup and view all the answers

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

<p>It should be approximately normal. (A)</p> Signup and view all the answers

<p>2.01 (D)</p> Signup and view all the answers

A statistical test used to determine if there is a significant difference between the means of two or more groups.

The hypothesis that there is no significant difference between the means of two or more groups.

The hypothesis that there is a significant difference between the means of two or more groups.

The probability of rejecting the null hypothesis when it is actually true.

A post-hoc test used to determine which specific groups differ significantly from each other after an ANOVA has shown a significant overall difference.

A statistical method used to reduce a large number of variables into a smaller set of underlying factors.

A statistical test that measures the relationship between two nominal variables. It determines if there's a significant association between the categories of the variables.

A statistical test that examines the relationship between two ordinal variables. It evaluates the strength and direction of the association, indicating whether the variables tend to increase or decrease together.

The degree to which multiple variables are linearly related. EFA requires sufficiently high correlations between variables.

A statistical test that measures the sampling adequacy for factor analysis. A value greater than 0.5 is generally acceptable.

A statistical test comparing two independent groups on a continuous variable to determine if there's a significant difference between their means.

A statistical test that tests the null hypothesis that the correlation matrix is an identity matrix. If significant, it suggests there are relationships between variables suitable for EFA.

Assumptions are specific conditions that must be met for a statistical test to be valid. If these assumptions are not met, the results might be unreliable.

A measure of internal consistency reliability for a scale. Generally, a Cronbach's Alpha value of 0.7 or higher indicates good reliability.

A measurement of the spread of data points around the mean. It is calculated by dividing the standard deviation by the mean and multiplying by 100.

A visual representation of data that shows the distribution of values, including the mean, quartiles, and outliers.

A statistical technique used to measure the strength and direction of the linear relationship between two interval-ratio variables.

A numerical value that represents the strength of the linear relationship between two variables. It ranges from -1 to +1, where -1 indicates a perfect negative correlation, +1 indicates a perfect positive correlation, and 0 indicates no correlation.

Values that lie significantly far from the rest of the data points, potentially skewing the analysis.

A technique to transform raw scores into standardized scores, making it easier to compare data from different scales.

The average value of a set of data points. It is often used to describe the central tendency of the data.

The degree to which data points are spread out around the mean. The more spread out, the higher the spread.

A test to determine if there is a significant relationship between two variables measured at least at the ordinal level.

The assumption that the relationship between two variables is not linear, requiring a non-parametric test like Spearman.

A visual representation of the distribution of data points in a scatter plot, showing whether the data points follow a linear trend.

The relationship between two variables can be interpreted by its direction and strength.

A statistical test used to compare the means of two related groups, where data is collected from the same subjects under two different conditions or at two different time points.

A non-parametric equivalent to the paired samples t-test, used when the data doesn't meet the assumptions of a parametric test.

A statistical test used to compare the means of two or more independent groups.

A statistical test used to compare the means of two or more independent groups when the assumptions of ANOVA are not met.

A statistical test used to compare the means of two related groups when data is collected from the same subjects under two different conditions or at two different time points. It is used to determine whether there is a significant difference between the two groups.

A non-parametric test used to compare the means of two related groups when the data doesn't meet the assumptions of a parametric test. It is used to determine whether there is a significant difference between the two groups.

A statistical test used to compare the means of two or more independent groups. This test determines whether there is a significant difference between the means of the groups.

A non-parametric test used to compare the means of two or more independent groups when the assumptions of ANOVA are not met. This test determines whether there is a significant difference between the means of the groups.