If f(x) = x^2/2-13, what is the value of f(6) ?

Need help ...,,.....,,........

Hatshy [7]

Answer:

i’m pretty sure that it’s 50. i haven’t done this in a awhile though. but pretty positive it’s 50

Step-by-step explanation: :)

6 0

3 years ago

Please help me! I will mark you as the best answer

zmey [24]

Answer:

75/4 = 18.75

Step-by-step explanation:

Because a squar is 4 sides add 75 is the perimiter

5 0

3 years ago

At a recent county fair, you observed that at one stand people's weight was forecasted, and were surprised by the accuracy (with

MatroZZZ [7]

Answer:

a)Slope: $\hat \beta_1 =\frac{7625.9}{1248.9}=6.106$

Intercept: $\hat \beta_o = 157.955 -6.106 (69.686)=-267.548$

b) $r=\frac{7625.9}{\sqrt{[1248.9][94228.8]}}=0.657$

And the determination coeffecient is $r^2 = 0.657^2 =0.432$

Step-by-step explanation:

Data given and definitions

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.

The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"

When we conduct a multiple regression we want to know about the relationship between several independent or predictor variables and a dependent or criterion variable.

n=110, $\sum x_i y_i = \sum (X-\bar X)(Y-\bar Y) =7625.9,\sum x^2_i=\sum (x-\bar x)^2 =1248.9 , sum y^2_i=\sum(y-\bar y)^2 =94228.8$

$\sum Y_i =17375 , \sum X_i = 7665.5$

Part a

The slope is given by this formula:

$\hat \beta_1 =\frac{\sum (x-\bar x) (y-\bar y)}{\sum (x-\bar x )^2}$

If we replace we got:

$\hat \beta_1 =\frac{7625.9}{1248.9}=6.106$

We can find the intercept with the following formula

$\hat \beta_o = \bar y -\hat \beta_1 \bar x$

We can find the average for x and y like this:

$\bar X=7665.5/110 =69.686, \bar y= 17375/110=157.955$

And replacing we got:

$\hat \beta_o = 157.955 -6.106 (69.686)=-267.548$

Part b

In order to calculate the correlation coefficient we can use this formula:

$r=\frac{\sum (x-\bar x)(y-\bar y) }{\sqrt{[\sum (x-\bar x)^2][\sum(y-\bar y)^2]}}$

For our case we have this:

n=110, $\sum x_i y_i = \sum (X-\bar X)(Y-\bar Y) =7625.9,\sum x^2_i=\sum (x-\bar x)^2 =1248.9 , sum y^2_i=\sum(y-\bar y)^2 =94228.8$

So we can find the correlation coefficient replacing like this:

$r=\frac{7625.9}{\sqrt{[1248.9][94228.8]}}=0.657$

And the determination coeffecient is $r^2 = 0.657^2 =0.432$

6 0

4 years ago

Roger claims that the two statistics most likely to change greatly when an outlier is added to a small data set are the mean and

Leni [432]

Answer:

No, the Roger’s claim is not correct.

Step-by-step explanation:

We are given that Roger claims that the two statistics most likely to change greatly when an outlier is added to a small data set are the mean and the median.

This statement by Roger is incorrect because the median is unaffected by the outlier value and only the mean value gets affected by the outlier value.

As the median represents the middlemost value of our dataset, so any value which is an outlier will be either at the start or at the end will not the median value. So, the median will not likely change when an outlier is added to a small data set.

Now, the mean is the average of all the data set values, that is the sum of all the observations divided by the number of observations. The mean will get affected by the outlier value because it take into account each and every value of the data set.

Hence, the mean will likely to change greatly when an outlier is added to a small data set.

7 0

4 years ago

Which is the graph of y = [x]-2?<br> Please please helped timed 20points

zubka84 [21]

Answer:

3rd graph

Step-by-step explanation:

5 0

3 years ago