What does it mean if r = 0?
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 6m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - Excel42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - Excel27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors15m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression3h 33m
- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - Excel8m
- Finding Residuals and Creating Residual Plots - Excel11m
- Inferences for Slope31m
- Enabling Data Analysis Toolpak1m
- Regression Readout of the Data Analysis Toolpak - Excel21m
- Prediction Intervals13m
- Prediction Intervals - Excel19m
- Multiple Regression - Excel29m
- Quadratic Regression15m
- Quadratic Regression - Excel10m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
1. Intro to Stats and Collecting Data
Intro to Stats
Problem 1.2.17b
Textbook Question
Happiness and Your Heart Is there an association between level of happiness and the risk of heart disease? Researchers studied 1739 people over a 10-year period and asked questions about their daily lives and the hassles they face. The researchers also determined which individuals in the study experienced any type of heart disease. After their analysis, they concluded that happy individuals are less likely to experience heart disease. Source: European Heart Journal 31 (9):1065–1070, February 2010.
What is the response variable? What is the explanatory variable?
Verified step by step guidance1
Step 1: Understand the context of the study. The researchers are investigating whether there is a relationship between happiness and the risk of heart disease over a 10-year period.
Step 2: Identify the response variable. The response variable is the outcome or the variable that the researchers are trying to explain or predict. In this case, it is whether or not an individual experiences heart disease.
Step 3: Identify the explanatory variable. The explanatory variable is the variable that is believed to influence or explain changes in the response variable. Here, it is the level of happiness of the individuals.
Step 4: Summarize the variables clearly: The response variable is the presence or absence of heart disease, and the explanatory variable is the level of happiness.
Step 5: Recognize that this setup allows researchers to analyze if happiness (explanatory) affects the likelihood of heart disease (response).
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Response Variable
The response variable is the outcome or dependent variable that researchers measure to see if it is affected by other factors. In this study, it is whether or not individuals experienced heart disease, as this is the health outcome being analyzed.
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Explanatory Variable
The explanatory variable is the independent variable that is believed to influence or explain changes in the response variable. Here, it is the level of happiness, as researchers are investigating if happiness affects the risk of heart disease.
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Association Between Variables
An association indicates a relationship or correlation between two variables, but it does not imply causation. This study examines whether there is an association between happiness and heart disease risk, meaning they look for patterns or links without necessarily proving one causes the other.
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