Given a scatterplot of versus for used sedans, what type of correlation would you most likely expect to observe between and ?
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: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 29m
- 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. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
11. Correlation
Scatterplots & Intro to Correlation
Problem 4.1.53
Textbook Question
Explain what is wrong with the following statement: “We have concluded that a high correlation exists between the gender of drivers and rates of automobile accidents.” Suggest a better way to write the sentence.
Verified step by step guidance1
Step 1: Understand that correlation measures the strength and direction of a linear relationship between two quantitative variables. Gender is a categorical variable, not quantitative, so calculating correlation with gender is inappropriate.
Step 2: Recognize that using the term 'correlation' implies a numerical measure like Pearson's correlation coefficient, which cannot be applied to categorical variables such as gender.
Step 3: Identify that the statement should instead refer to an association or relationship between gender (a categorical variable) and accident rates (which could be quantitative or categorical).
Step 4: Suggest rephrasing the sentence to say: 'We have found a significant association between the gender of drivers and rates of automobile accidents,' which correctly reflects the type of relationship without implying a correlation coefficient.
Step 5: Optionally, if accident rates are numerical, consider using comparative statistics (like mean accident rates by gender) or categorical association measures (like chi-square test) to describe the relationship appropriately.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Correlation and Causation
Correlation measures the strength and direction of a linear relationship between two variables but does not imply that one causes the other. Misinterpreting correlation as causation can lead to incorrect conclusions about relationships between variables.
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Appropriate Use of Variables in Correlation
Correlation requires numerical variables; gender is a categorical variable and cannot be directly correlated with another variable. Instead, comparisons should use methods suitable for categorical data, such as contingency tables or group comparisons.
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Clear and Accurate Statistical Reporting
Statistical statements should precisely describe the relationship and the method used. A better sentence might specify differences in accident rates between genders rather than implying a correlation, ensuring clarity and correctness.
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