The only difference is that we specify which IV is within-subjects by placing it in the error term:Īov(DV ~ IVB * IVW + Error(Subjects/IVW, data) library(xtable) The formula for running a mixed design ANOVA is very similar what we have seen before.
Additionally, taking pictures or not, may have no influence on memory for the statements in the audio guide. The dependent measure was performance on the memory test.Īn overarching question was whether or not participants would have better visual memory for exhibit objects when they took pictures, compared to when they didn’t. IV2 was a within-subject manipulation of memory test (visual vs. audio). IV 1 was a between-subjects manipulation involving picture-taking (camera vs. no camera). They were also given an auditory recognition test containing statements that could have been on the audio guide, and they had to identify which ones they had heard before. They were given a visual recognition test containing pictures of objects, and were asked to identify which objects they remembered seeing. At this point they were given two memory tests for the things they saw and heard in the exhibit. Additionally, while visiting the exhibit, participants listened to audio guides about the things the were looking at.Īfter participants were done with the exhibit the returned to the sign-in desk. They freely looked at anything in the exhibit, and were allowed to take pictures of anything they wanted (if they were in the camera condition). Half of the participants were allowed to take photographs (with camera, at least 10 pictures) and the other half were not (no camera). In Experiment 1, participants visited a museum exhibit. 11.6.2 Conduct a Mixed-Factorial Analysis of Variance (ANOVA).11.4.4 Get the data into the format you want.11.1 Do you remember things better when you take pictures of them?.10.6.4 Conduct a Repeated Measures Two-Factor Analysis of Variance (ANOVA).10.6.2 Conduct a Between-Subjects Two-Factor Analysis of Variance (ANOVA).10.4.4 Get the data into the format you want.10.1 Does standing up make you focus more?.9.6.4 Conduct planned comparisons using a paired-samples t-test.9.6.3 Conduct and graph One-Factor Repeated Measures ANOVA.9.6.2 Produce a frequency histogram and remove outliers.9.4.6 Conduct the repeated Measures ANOVA.9.1 Betcha can’t type JHDBZKCO very fast on your first try.8.6.4 Unplanned Comparisons: Post-hoc tests.8.6.2 Performing a One-Factor Analysis of Variance (ANOVA) & Graphing the data.8.1 How to not think about bad memories by playing Tetris.7.6.2 Performing an independent-samples t-test.7.4.7 Reconstructing the graph from the paper.7.4.5 Conduct Independent samples t-test.7.1 Do you come across as smarter when people read what you say or hear what you say?.6.6.5 The relationship between the one-sample and the paired-samples t-test.6.6.3 Performing a paired-samples t-test.6.4.4 Baseline phase: Conduct a one sample t-test.6.1 Does Music Convey Social Information to Infants?.6 Lab 6: t-Test (one-sample, paired sample).5.3.4 Entering data for sign test problems.5.3.2 Calculate difference scores between pairs of measures.5 Lab 5: Fundamentals of Hypothesis Testing.4.4.1 Saving data as standardized values.
4.2.3 Sampling distributions for any statistic.4.2.2 sampling distribution of the mean.4 Lab 4: Normal Distribution & Central Limit Theorem.3.4.1 Correlation Coefficient for Bivariate Data: Two Variables.2.4.2 Descriptive Statistics and Histograms.