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Define and distinguish among positive correlation, negative correlation, and no correlation. Give an example of each type of correlation. B. Positive correlation means that two variables tend to change in opposite directions, with one increasing while the other decreases. An example might be age and vision. be the diameter of a circle and its circumference. Dositive correlation means that both variables tend to increase (or decrease) together. An example might be shoe size and height. might be hair color and weight. Define negative correlation. Choose the correct answer below. A. Negative correlation means that both variables tend to increase (or decrease) together. An example might be shoe size and height.

Ask by Welch Warren. in the United States
Mar 09,2025

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**Positive Correlation:** - **Definition:** Two variables increase or decrease together. - **Example:** Diameter and circumference of a circle. **Negative Correlation:** - **Definition:** One variable increases while the other decreases. - **Example:** Age and vision quality. **No Correlation:** - **Definition:** Changes in one variable do not affect the other. - **Example:** Hair color and weight.

Solution

**Step 1. Define Positive, Negative, and No Correlation** - **Positive correlation:** Two variables exhibit a positive correlation if, when one variable increases, the other variable tends to increase as well, and vice versa. *Example:* The diameter \( d \) and the circumference \( C \) of a circle are positively correlated because \( C = \pi d \); as the diameter increases, the circumference increases too. - **Negative correlation:** Two variables have a negative correlation if, when one variable increases, the other variable tends to decrease, and vice versa. *Example:* Consider age and vision quality. As age increases, vision quality tends to decline, thus exhibiting a negative correlation. - **No correlation:** Two variables have no correlation if changes in one variable do not predict any specific changes in the other. *Example:* Hair color and weight have no systematic relationship, so they are uncorrelated. **Step 2. Correcting the Misconception** In the provided statements, there is a mix-up: - The statement “Positive correlation means that two variables tend to change in opposite directions” is incorrect. In fact, positive correlation means that the variables increase (or decrease) together. - The correct definition of negative correlation is that as one variable increases, the other decreases. **Step 3. Answer the Specific Question on Negative Correlation** The correct answer for defining negative correlation is: - **Negative correlation means that as one variable increases, the other variable tends to decrease (and vice versa).** Thus, the statement “Negative correlation means that both variables tend to increase (or decrease) together” is incorrect.

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Bonus Knowledge

Positive correlation means that both variables move in the same direction—when one increases, the other does too! A classic example is height and shoe size; generally, taller individuals tend to have larger feet. On the flip side, negative correlation shows that as one variable increases, the other decreases. For instance, the amount of gas in your tank and the distance you can drive create a negative correlation: as you drive further, your gas level decreases. No correlation indicates no discernible relationship between the two variables, like the color of your shirt and the number of shoes you own; there's simply no connection! To avoid common misconceptions, it's essential to remember that correlation does not imply causation! Just because two things seem linked doesn’t mean one causes the other. For instance, ice cream sales and drowning rates may rise together in summer, but that doesn’t mean buying ice cream causes drowning incidents! Always analyze the context behind the data and look for other factors that might play a role.

Related Questions

Question 12(Mulliple Choice Warth 5 points) \[ (04.06 \mathrm{HC}) \] A researcher wants to test the claim that the proportion of juniors who watch television regularly is greater than the proportion of seniors who watch television regularly She finds that 56 of 70 randomly selected juniors and 47 of 85 randomly selected seniors report watching television regularly. Construct \( 95 \% \) confidence intervals for each population proportion. Which of the statemente gives the correct outcome of the research or's tert of the dalim? The \( 95 \% \) confidence interval for juniors is (706, 894), and the \( 95 \% \) confidence interval for seniors is ( 447,659 ). Since the intervals overlap, there is not enough evidence to say the proportion of juniors who watch television regularly may be higher than that of seniors. The \( 95 \% \) confidence interval for juniors is (721, 879), and the \( 95 \% \) confidence interval for seniors is (464, 642). Since the interval for juniors is higher than the interval for seniors, there is evidence to say the proportion of juniors who watch television regularly may be higher than that of seniors. The \( 95 \% \) confidence interval for juniors is ( 706,894 ), and the \( 95 \% \) confidence interval for seniors is ( 447,659 ). Since the interval for juniors is higher than the interval for seniors, there is evidence to say the proportion of juniors who watch television regularly may be higher than that of seniors. The \( 95 \% \) confidence interval for juniors is ( \( 721, .879 \) ), and the \( 95 \% \) confidence interval for seniors is (464, 642). Since the intervals overlap, there is not enough evidence to say the proportion of juniors who watch television regularly may be higher than that of seniors.

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