Statistical Sciences 1024A/B Chapter Notes - Chapter 4: Blood Alcohol Content, Dependent And Independent Variables, Scatter Plot

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salmonlocust315

20 Apr 2017

School

Western University

Department

Statistical Sciences

Course

Statistical Sciences 1024A/B

Professor

Lori Murray

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Document Summary

A response variable measures an outcome of a study. These can also be called independent variables or predictor variables. An explanatory variable may explain or influence changes in a response variable. Students drake different number of cans of beers and 30 mins later a police officer measured their blood alcohol content. The number of beers consumed is the explanatory variable (dependent) Percent of alcohol in the blood is the response variable (independent) A sociologist looks at the same data using the amount of debt and income, along with other variables. Income and debt are explanatory variables and stress levels are response variables. The most useful graph for displaying the relationship between 2 quantitative variables is a scatterplot. It shows the relationship between 2 quantitative variables measured on the same individuals. The values of one variable appear on the horizontal axis, and the values of the other variable appear on the vertical axis.

Related Questions

Inalize three research questions relating to your selected dataset. Make sure the variables used in the final questions you select are of the following format:
1. Continuous response and continuous explanatory variable
2. Categorical response and categorical explanatory variable
3. Continuous response and categorical explanatory variable (note: the categorical variable must be dichotomous for this question)
Each research question should have a clear explanatory and response variable. Review, as necessary, the ‘Laerd Statistics’ reading from last week which explains data types and the difference between response variables (also referred to as dependent or outcome variables) and explanatory variables (also referred to as independent or predictor variables).
Then, in your initial post, list your three finalized research questions, indicating the variable types.
For example, using data from the Framingham Heart Study dataset, one question might be: ‘Is there a significant difference in total serum cholesterol levels [TOTCHOL] (continuous-ratio) (response) between smokers and non-smokers [CURSMOKE] (categorical-dichotomous) (explanatory)?’
In your response post to your peers, provide feedback on their finalized research questions, which will become the foundation of each student’s final project. Consider the following questions as you review your peers' research questions:
• Is each research question clearly stated?
• Does each research question relate to the dataset?
• Do the three research questions meet the data type requirements?
• Does each research question identify response and explanatory variables correctly?

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Statistical Sciences 1024A/B Chapter Notes - Chapter 4: Blood Alcohol Content, Dependent And Independent Variables, Scatter Plot

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