You use a line of best fit for a set of data to make a prediction about an unknown value. The correlation coefficient for your data set is -0.833. Can you be confident that your predicted value will be reasonably close to the actual value? Why or why not?

The correlation Coefficient gives the measure of the strength and direction of the relationship between two variables. - 0.833 depicts a strong negative relationship. Hence, one can be confident that the predicted value will be close to the actual Value.

The Correlation Coefficient, R ranges from - 1 to 1, with values closer to - 1 and 1 representing strong negative and positive relationship respectively, which is only achieved of the data is modeled very well.

Therefore, since, - 0.833 is a strong correlation Coefficient, then we can be confident in the predicted value.

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As, given correlation coefficient for your data set is= -0.015

It means there is weak relation between two variables.If value of correlation coefficient is near to 1 or -1, it shows there is strong correlation.

Negative correlation means, if one quantity is increasing other is decreasing.So, the value of -0.015 shows that there is very less correlation between x and y values or two values in data set.

So, the chances are very less that predicted value will be reasonably close to the actual value as the points will be far from line of best fit.

Step-by-step explanation:

fourth month

step-by-step explanation:

it is the one with the most keychains.

93.8

step-by-step explanation:

lets say, first number = x

second number = 3x+7

total = 49

(x)+(3x+7)= 49

4x+7 = 49

4x = 42

x = 42/4

x= 10.5

x= 10.5

3x+7 = 3(10.5)+7 = 93.8

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