Which characteristic of a data set makes a linear regression model unreasonable?
Answer: A correlation coefficient close to zero makes a linear regression model unreasonable.
If the correlation between the two variable is close to zero, we can not expect one variable explaining the variation in other variable. For a linear regression model to be reasonable, the most important check is to see whether the two variables are correlated. If there is correlation between the two variable, we can think of regression analysis and if there is no correlation between the two variable, it does not make sense to apply regression analysis.
Therefore, if the correlation coefficient is close to zero, the linear regression model would be unreasonable.
Ok so this can get tricky, it is basically just asking for you to perform many unit conversions. I'll try to simplify it for you here while still maintaining the explanation. If you have any questions about this process feel free to message me.
3 yards = ____ miles (conversion factor is 1760 because there are 1760 yards in a mile)
3/1760 = 0.017 miles,
Now we just need to convert seconds to hours.
1 second is how many mins, then how many mins in an hour?
360 seconds in an hour.
Ok now we just need to combine these two pieces of info,
0.017/360 = 4.72222 miles per hour. Thus 4.72 is the answer.
Answer:
L times W times H
Step-by-step explanation:
just multiply the length times the width times the height
Division and multiplication
Answer:
gay
Suppose we have a simple random sample of 400 households drawn from a city with 40,000 households . A 95% confidence interval estimate for the population mean number of children per household is [1.1,2.3]. Given this, what is the lower confidence limit for the total number of children in the city
