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notka56 [123]
3 years ago
7

How do you compare two ratios

Mathematics
1 answer:
serious [3.7K]3 years ago
7 0

Answer:

how you can divide them I believe

Step-by-step explanation:

you need to divided both of them to see a difference

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Find the average of 8.4 7.5 12.9 and 10.6 also the method how to do it​
SashulF [63]
Find the average :8.4+7.5+12.9+10.6 divided by four
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3 years ago
y is inversely proptional to x when y = 7, x = 9 a) work out an equation connecting y and x b) work out the value of y when x =
OLga [1]

Answer:

a) yx=63

b) y=3

Step-by-step explanation:

a)

yx=k (inverse formula)

7(9)=k

63=k

b)

y(21)=63

y=63/21

y=3

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3 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
A multiple choice test has four possible answers for each question. Let X be the number of correct responses in a test of 100 qu
dimulka [17.4K]

Answer:

a. 4.33.

Step-by-step explanation:

If there is only one correct answer out of four alternatives, the expected proportion of correct answers is p =0.25

Sample size (n) = 100 questions

The standard deviation of a proportion 'p' is given by:

s=\sqrt{\frac{p*(1-p)}{n} }

Applying the given data:

s=\sqrt{\frac{0.25*(1-0.25)}{100}}\\s=0.0433

If X is the number of correct responses in 100 guesses, the standard deviation of X is:

\sigma = n*s=100*0.0433\\\sigma = 4.33

The standard deviation of X is 4.33 questions.

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3 years ago
Jenny’s mom gave her one dollar on the day she was born. She plans to triple the amount she gives her every day. How much will s
astraxan [27]

Answer:

19,683

Step-by-step explanation:

3 0
3 years ago
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