How do I solve this ?

Which of the following data sets indicates a strong negative correlation?

Nuetrik [128]

Answer:

Option: C is the correct answer.

C. {(-2, 4), (-1, 2), (0, 0), (1, -2) }

Step-by-step explanation:

<u>Strong negative correlation--</u>

A negative correlation is a relationship between two variable such that with the increase of one variable the other variable decrease and vice versa.

Negative correlation is also means the two variables have an inverse relationship.

Also, the relationship is strong if all the points lie above the line of best fit.

Hence, from the given set of data the set that represent the strong negative correlation is:

C. {(-2, 4), (-1, 2), (0, 0), (1, -2) }

Since in this set the x-value is increasing by a constant rate i.e. 1 ( i.e. -2,-1,0 and 1) while the other value is decreasing by a constant rate i.e. 2 ( i.e. 4,2,0 and -2).

Hence, we will get a linear relationship such that all the points will lie above the line and the line of best fit have a negative slope.

Hence, the data set has a strong negative correlation.

6 0

3 years ago

Read 2 more answers

Kiley gathered the data in the table. She found the approximate line of best fit to be y = 1.6x – 4. A 2-column table with 5 row

Dimas [21]

Answer:

The residual value is -1.8 when x = 3

Step-by-step explanation:

We are given the following table

x | y

0 | -3

2 | -1

3 | -1

5 | 5

6 | 6

Residual value:

A residual value basically shows the position of a data point with respect to the line of best fit.

The residual value is calculated as,

Residual value = Observed value - Predicted value

Where observed values are already given in the question and the predicted values are calculated by using the equation of line of best fit.

$y = 1.6x - 4$

When we substitute x = 3 in the above equation then we would get the predicted value.

$y = 1.6x - 4 \\\\y = 1.6(3) - 4 \\\\y = 4.8 - 4 \\\\y = 0.8$

So the predicted value is 0.8

From the given table, the observed value corresponding to x = 3 is -1

So the residual value is,

Residual value = Observed value - Predicted value

Residual value = -1 - 0.8

Residual value = -1.8

Therefore, the residual value is -1.8 when x = 3

Note: A residual value closer to 0 is desired which means that the regression line best fits the data.

5 0

3 years ago

Read 2 more answers

Pahelp naman po

MakcuM [25]

Answer:

81.5+2.6=84.1

understand: we have to add the weight lost to her current weight to find the original weight.

plan: first we take 81.5 and add the weight lost to it 2.6

solution: 81.5+2.6=84.1

check: 84.1-2.6=81.5

:]

3 0

3 years ago

7. A recent medical survey reported that 45% of the respondents felt that the doctor explained their condition in a sufficient m

vovikov84 [41]

Answer:

a)0.866

b)0.9623

Step-by-step explanation:

8 0

3 years ago

Margot gave 10% of x number of dollars that she earned over the summer to an animal rescue shelter. 10% of x is about $60.00. Ch

AysviL [449]

A, C, and E seem all right. In letter form: 1st 3rd and 5th

3 0

3 years ago