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bija089 [108]
3 years ago
5

Based on this information, which statement BEST describes the relationship between literacy rates and a nation's standard of liv

ing? A) Literacy rates have very little effect on economic production and standard of living. B) A higher literacy rate will have a positive effect on a nation's standard of living. C) A nation's standard of living is totally dependent on its educational system. D) Overpopulation has a negative impact on GDP and literacy rates.
Mathematics
1 answer:
Dafna11 [192]3 years ago
4 0

Answer: the answer is B

Step-by-step explanation:

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Find the 15th term of the arithmetic sequence 13,8,3,-2
Lunna [17]

Answer:

-57

Step-by-step explanation:

13,8,3,-2 (decreasing by 5)

13,8,3,-2,-7,-12,-17,-22,-27,-32,-37,-42,-47,-52,-57.

The 15th term is -57.

<u><em>Ace</em></u>

4 0
2 years ago
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
3 years ago
Ms. jones is 50bls over weight. she decided to follow a diet to lose 50% of her excess weight by the first month, 20% by the end
sladkih [1.3K]

Answer:

5%

Step-by-step explanation:

You sum the lost excess weight: 50% + 20% + 25% = 95%. Meaning that she lost 95% of the excess weight. It remained just 5% to lose.

8 0
3 years ago
A circle with radius of 3cm sits inside a 8 cm x 7cm rectangle what is the area of the shaded region?
Temka [501]

Answer:

You have to say which one is the shaded region the circle or the rectangle

Step-by-step explanation:

5 0
3 years ago
Emma is eating a bowl of soup for dinner. She estimates the bowl holds 2 quarts of soup . Do you think Emma's estimate is reason
FinnZ [79.3K]

Emma's estimate is not reasonable because a serving of soup is typically about 1-2 cups and 2 quarts = 8 cups.

would you eat 8 cups of soup? no.
4 0
3 years ago
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