Given the data set for the length of time a person has been jogging and the person's speed, hypothesize a relationship between the variables.
a) I would expect the data to be positively correlated
b) I would expect the data to be negatively correlated**
c) I would expect no correlation
d) there is not enough information
@bobpursley
I agree.
Based on the given information, it is difficult to hypothesize the relationship between the variables without knowing the actual data or having further information. Therefore, the correct answer is d) there is not enough information.
To hypothesize a relationship between the variables, you would need to analyze the data set for the length of time a person has been jogging and the person's speed. Here are the steps you can follow to make your hypothesis:
1. Start by plotting the data points on a scatter plot, with the length of time on the x-axis and the speed on the y-axis.
2. Look at the overall trend of the data points on the scatter plot. If the points tend to form a clear pattern that either increases or decreases as the length of time increases, there may be a correlation.
3. Calculate the correlation coefficient, such as the Pearson correlation coefficient, to quantify the relationship between the variables. The correlation coefficient will indicate the strength and direction of the relationship.
- If the correlation coefficient is close to +1, it suggests a strong positive correlation, meaning that as the length of time increases, the speed also tends to increase.
- If the correlation coefficient is close to -1, it suggests a strong negative correlation, meaning that as the length of time increases, the speed tends to decrease.
- If the correlation coefficient is close to 0, it suggests no correlation, meaning that there is no clear relationship between the length of time and speed.
Based on your given options, it seems like the correct answer would be:
b) I would expect the data to be negatively correlated.