stat10010lab3.pdf

# Lets look at the otis scores by education group go to

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Let’s look at the Otis scores by education group. Go to Graph -> Boxplot. Under the One Y option choose With Groups. Place Otis in the Graph Variables box and Education in the Categorical variables for grouping box . Add a title to your plot. Q8: Comment on the relationship between the Otis scores and the education of the participants. Q9: Create a box-and-whisker plot to help answer the following question. Does watching the cartoon characters in colour influence the learning of participants immediately after viewing the lecture slides? 7. Construct a bar plot. Let’s create a bar plot of the categorical variable Education which records the type of education level of each participant. Go to Graph -> Bar Chart and tell Minitab that the bars represent counts of unique values. Choose a Simple bar chart and plot the education variable. Q10: Which is the most frequent type of education level in the set of study participants?

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8. Create a contingency table. We saw in class that a good way to summarise two categorical variables is by using a two way table (often called a contingency table ). Let’s cross-tabulate the Education variable with the Location variable. Recall what the different categories in each of these variables are. To create a table, go to Stat->Tables->Cross Tabulation and Chi-Square… Put the Education variables in the rows of the table and the Location variable in the columns. The resulting table should appear in your session window similar to that shown below. Q11: Does the table tell you anything about the set of study participants? For example, would you make any comment on the relationship between non-medical staff and Hospital C? oOo You now have now worked with a large data set involving both categorical and numerical data, and you have summarized this large data set using illustrative plots and tables. It has been easier for you to draw conclusions about the question under study from the illustrative plots and tables than it would have been by just looking at the rows of raw data. Even more steps into the world of a statistician … oOo
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