Research Design and Statistics Course Quiz

<p>The type of measurement (categorical or continuous). (C)</p> Signup and view all the answers

<p>To ensure the application of an appropriate statistical test that is related to the aim and data. (A)</p> Signup and view all the answers

<p>Carrying out statistical tests using SPSS and interpreting data. (A)</p> Signup and view all the answers

<p>To develop confidence in your ability to find the best analysis method for your data. (B)</p> Signup and view all the answers

<p>Statistics are used to test a hypothesis based on a model of the data. (A)</p> Signup and view all the answers

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

<p>Correlation or Regression (B)</p> Signup and view all the answers

<p>When comparing means of multiple related groups over one factor (D)</p> Signup and view all the answers

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

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

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

<p>Kruskal-Wallis test (D)</p> Signup and view all the answers

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

<p>A design with two or more independent variables (C)</p> Signup and view all the answers

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

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

<p>Equal intervals between values and a defined zero point. (B)</p> Signup and view all the answers

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

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

<p>The type of both outcome and predictor variables (A)</p> Signup and view all the answers

<p>Determining the type of measurement (C)</p> Signup and view all the answers

<p>Ratio variables have a true zero point, while interval variables do not. (A)</p> Signup and view all the answers

<p>The divisions on the Likert scale were considered to be equal approximately (B)</p> Signup and view all the answers

<p>The studies are inconclusive with some suggesting effectiveness of antiSTATIC and others suggesting there is no difference. (C)</p> Signup and view all the answers

<p>AntiSTATic is only as successful in reducing anxiety as the control. (B)</p> Signup and view all the answers

<p>The finding is open to more than one interpretation and further study is needed. (D)</p> Signup and view all the answers

<p>Consider the overall pattern of results and note the research is inconclusive with mixed results. (A)</p> Signup and view all the answers

<p>The test taker distrusts their initial analysis and is unsure of choosing the most obvious answer. (C)</p> Signup and view all the answers

<p>Always has a mean of zero (C)</p> Signup and view all the answers

<p>Mean &gt; Median &gt; Mode (D)</p> Signup and view all the answers

<p>The peakedness or flatness of the distribution (B)</p> Signup and view all the answers

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

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

<p>The distribution is relatively flat and wide. (C)</p> Signup and view all the answers

<p>Mean = Median = Mode (B)</p> Signup and view all the answers

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

<p>The extent to which a measure assesses what it is intended to assess. (C)</p> Signup and view all the answers

<p>The ability of a measure to produce stable scores when administered at two time points. (C)</p> Signup and view all the answers

<p>Differences in performance directly caused by the experimental manipulation. (A)</p> Signup and view all the answers

<p>The independent variable is a cause; whereas the dependent variable is an effect. (B)</p> Signup and view all the answers

<p>That there is no effect of the predictor variable on the outcome variable. (A)</p> Signup and view all the answers

<p>The probability that the null hypothesis is true. (C)</p> Signup and view all the answers

<p>The direction of the difference between groups. (B)</p> Signup and view all the answers

<p>A significant result always indicates a practically important effect. (D)</p> Signup and view all the answers

<p>The idea that statistical significance is the only criteria to consider; irrespective of effect size. (C)</p> Signup and view all the answers

<p>Variations due to unknown random factors such as measurement error, or time of day (A)</p> Signup and view all the answers

The type of data being measured, either continuous (e.g., height, weight) or categorical (e.g., gender, colour).

The number of variables that are influencing or predicting the outcome, for example, if you are looking at the effect of age and gender on reaction time, you would have two predictor variables.

The hypothesis that is being tested using statistical analysis. It usually proposes a relationship between variables.

The specific method of statistical analysis used to test the hypothesis based on the type of data and the number of predictor variables.

The design of the study is crucial to ensure the data collected is relevant and reliable for testing the hypothesis.

The process of gathering information related to the hypothesis, for example, conducting experiments or surveys.

The analysis of the collected data using statistical methods to determine if the hypothesis is supported or rejected.

Interpreting the results of the statistical analysis, making conclusions about the hypothesis, and considering limitations of the study.

A variable where the difference between two values holds the same meaning regardless of its location on the scale. For example, the difference between 600ms and 800ms is the same as the difference between 1300ms and 1500ms.

A type of variable where the categories have a natural, logical order. For example, a Likert scale (strongly disagree, disagree, neutral, agree, strongly agree) or exam grades (fail, pass, merit, distinction) are ordinal variables.

A type of variable where the categories have no inherent order. For example, a variable representing favorite colors (red, blue, green, yellow) is a nominal variable.

A variable that can take on any value within a given range, including decimals. For example, height, weight, and time are continuous variables.

Variables used in statistical analysis to predict an outcome. They can be either continuous or categorical

A variable that is being measured or analyzed in a study.

A decision-making tool used in statistical analysis to help determine which statistical test is appropriate for a given research question.

A variable that can only take on a limited number of values, often representing distinct categories.

A statistical test designed to compare the means of two groups when the data is normally distributed and the variances are equal.

A statistical test used to compare the means of two related groups, like comparing the scores before and after an intervention.

A statistical test used to determine if there is a statistically significant difference between the means of two or more groups. It assumes the data is normally distributed and the variances are equal.

A statistical test used to compare the means of two or more groups, where each subject is measured multiple times under different conditions.

A statistical test used to examine the relationship between two continuous variables. It assumes a linear relationship between the variables.

A statistical test used to examine the relationship between two ordinal variables. It measures the strength and direction of the monotonic relationship between the variables.

When studies produce contradictory results, making it difficult to draw a definitive conclusion.

The difference between the average outcome of a treatment group and the average outcome of a control group.

The statistical significance of a result, typically represented by a p-value. Often, a p-value less than 0.05 indicates a significant finding.

Describes a group that doesn't receive the treatment being studied, used as a comparison point.

When multiple studies on the same topic yield inconsistent findings, making it difficult to reach a definitive conclusion.

A measure is valid if it accurately measures the specific concept it intends to assess. It avoids measuring other unintended elements.

Reliability ensures consistent results under the same conditions, showing a measurement's stability over time and across different uses.

Test-retest reliability refers to the consistency of scores over time when the same measure is administered on two separate occasions to the same group.

Systematic variation is a change in performance directly influenced by the experimental manipulation; it's the difference we intend to observe.

Unsystematic variation refers to variations in performance caused by unknown factors that might affect the results unintentionally.

Randomization is a technique used to minimize the influence of unsystematic variation by randomly assigning participants to treatment groups, creating more equal groups.

The Independent Variable (IV) is the presumed cause, the factor that is manipulated or changed in an experiment.

The Dependent Variable (DV) is the proposed effect, the change that is observed or measured in response to the independent variable.

The null hypothesis claims that there is no effect of the independent variable on the dependent variable.

The alternative hypothesis proposes that there is an effect of the independent variable on the dependent variable.

A symmetrical bell-shaped distribution where most values cluster around the mean, with decreasing frequency as you move further away from the mean.

The mean and standard deviation are the two parameters that define and shape the normal distribution.

A measure of central tendency that is the sum of all values divided by the number of values. It's the average of the data set.

A measure of data dispersion that describes how spread out the data points are relative to the mean.

A perfectly symmetrical distribution has the mean, median and mode all at the same point. Half of the measurements are above and half are below.

Skewness describes the asymmetry of a distribution. It indicates whether the tail of the distribution is longer on one side than the other.

A measure of the peakedness of a distribution. It describes how concentrated the data is around the center.

This describes the shape of the distribution with the highest point at the mean and the data points becoming less frequent with increasing distance from the mean.