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3241004551 [841]
3 years ago
6

The weights of 5 girls are 70 pounds, 68 pounds, 85 pounds, 62 pounds, and 70 pounds. Nina finds measures of center and measures

of variation of this data. Match the descriptions to the type of measure.
The options are,
She found the mean and then
found the average deviation of
the weights from the mean.
She found the middle value after
arranging all the values from least
to greatest.

She found the difference of the
upper quartile and the lower
quartile.

She found the value that appeared the
most often.

She found the difference of the least
and the greatest values.
She added all the values and divided the
sum by 5.
And the categories to put them into are,
Measure of Center or Measure of Variation.
Mathematics
1 answer:
Andru [333]3 years ago
4 0

Answer:

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njvlhvv lxflbif not.noting Ljubljana have pizza

justjust Nolvadex jfljjflj like luv the first to write you an opportunity. if I could see it as a result of the most important thing in my mind, and then you have a lot more to do it, I will have the option. if I could see it as an option for a long day of the day, I will have the option. if I could see it as an option for a long day of the most important thing is that the company. we will 4th. 4G and a lot more 5311iggtxtch ok I am going through 7-Eleven I was just a few wggch yeeks, and I will be the same thing 6.

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1.92/8 = .24 and more stuff like that.

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DEF rotates 90 degrees clockwise about point A to create D’E’F. Therefore, which equation must be true
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Thus, when ΔDEF rotates 90° clockwise about point A to create ΔD 'E 'F.

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Suppose you are interested in the effect of skipping lectures (in days missed) on college grades. You also have ACT scores and h
DIA [1.3K]

Answer:

a) For this case the intercept of 2.52 represent a common effect of measure for any student without taking in count the other variables analyzed, and we know that if HSGPA=0, ACT= 0 and skip =0 we got colGPA=2.52

b) This value represent the effect into the ACT scores in the GPA, we know that:

\hat \beta_{ACT} = 0.015

So then for every unit increase in the ACT score we expect and increase of 0.015 in the GPA or the predicted variable

c) If we are interested in analyze if we have a significant relationship between the dependent and the independent variable we can use the following system of hypothesis:

Null Hypothesis: \beta_i = 0

Alternative hypothesis: \beta_i \neq 0

Or in other wouds we want to check if an specific slope is significant.

The significance level assumed for this case is \alpha=0.05

Th degrees of freedom for a linear regression is given by df=n-p-1 = 45-3-1 = 41, where p =3 the number of variables used to estimate the dependent variable.

In order to test the hypothesis the statistic is given by:

t=\frac{\hat \beta_i}{SE_{\beta_i}}

And replacing we got:

t = \frac{-0.5}{0.0001}=-5000

And for this case we see that if we find the p value for this case we will get a value very near to 0, so then we can conclude that this coefficient would be significant for the regression model .

Step-by-step explanation:

For this case we have the following multiple regression model calculated:

colGPA =2.52+0.38*HSGPA+0.015*ACT-0.5*skip

Part a

(a) Interpret the intercept in this model.

For this case the intercept of 2.52 represent a common effect of measure for any student without taking in count the other variables analyzed, and we know that if HSGPA=0, ACT= 0 and skip =0 we got colGPA=2.52

(b) Interpret \hat \beta_{ACT} from this model.

This value represent the effect into the ACT scores in the GPA, we know that:

\hat \beta_{ACT} = 0.015

So then for every unit increase in the ACT score we expect and increase of 0.015 in the GPA or the predicted variable

(c) What is the predicted college GPA for someone who scored a 25 on the ACT, had a 3.2 high school GPA and missed 4 lectures. Show your work.

For this case we can use the regression model and we got:

colGPA =2.52 +0.38*3.2 +0.015*25 - 0.5*4 = 26.751

(d) Is the estimate of skipping class statistically significant? How do you know? Is the estimate of skipping class economically significant? How do you know? (Hint: Suppose there are 45 lectures in a typical semester long class).

If we are interested in analyze if we have a significant relationship between the dependent and the independent variable we can use the following system of hypothesis:

Null Hypothesis: \beta_i = 0

Alternative hypothesis: \beta_i \neq 0

Or in other wouds we want to check if an specific slope is significant.

The significance level assumed for this case is \alpha=0.05

Th degrees of freedom for a linear regression is given by df=n-p-1 = 45-3-1 = 41, where p =3 the number of variables used to estimate the dependent variable.

In order to test the hypothesis the statistic is given by:

t=\frac{\hat \beta_i}{SE_{\beta_i}}

And replacing we got:

t = \frac{-0.5}{0.0001}=-5000

And for this case we see that if we find the p value for this case we will get a value very near to 0, so then we can conclude that this coefficient would be significant for the regression model .

7 0
2 years ago
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