Find the quotient -88, 11

Rachel can make 3 bracelets in an hour. Oliver can make only 2 bracelets in an hour, but he already has completed 5 bracelets. E

Sidana [21]

For the answer to the question above, Since Rachel makes 3 bracelets an hour, her linear equation should be y=3h. 3 represents the rate of change and h represents the number of hours as a variable.
Oliver's linear equation is y=2h+5 because 2 is the rate of change and 5 is the b value or the y-intercept in a linear equation y=mx+b. To find when both have the same number of bracelets, we find the point of intersection...
2h+5=3h
5=3h-2h
5=h
Therefore in 5 hours, both will have the same amount of bracelets.

7 0

3 years ago

Consider the dot plot which shows the distribution of data collected on the amount of time Jason sleeps each night. Find the dif

Tatiana [17]

Answer:

A) 0.2

Step-by-step explanation:

From least to greatest, the data points are

6, 6, 6, 7, 7, 7, 8, 8, 8, 9

To find the mean, we find the sum of the data points and divide by the number of data points, 10. The sum of the data points is

6+6+6+7+7+7+8+8+8+9 = 72

Dividing by 10, the mean is 72/10 = 7.2.

The median is the middle number in the set. This is 7.

The difference between the mean and the median is

7.2-7 = 0.2.

8 0

3 years ago

Health insurance benefits vary by the size of the company (the Henry J. Kaiser Family Foundation website, June 23, 2016). The sa

xxMikexx [17]

Answer:

$\chi^2 = \frac{(32-42)^2}{42}+\frac{(18-8)^2}{8}+\frac{(68-63)^2}{63}+\frac{(7-12)^2}{12}+\frac{(89-84)^2}{84}+\frac{(11-16)^2}{16}=19.221$

Now we can calculate the degrees of freedom for the statistic given by:

$df=(rows-1)(cols-1)=(3-1)(2-1)=2$

And we can calculate the p value given by:

$p_v = P(\chi^2_{2} >19.221)=0.000067$

And we can find the p value using the following excel code:

"=1-CHISQ.DIST(19.221,2,TRUE)"

Since the p values is higher than a significance level for example $\alpha=0.05$ , we can reject the null hypothesis at 5% of significance, and we can conclude that the two variables are dependent at 5% of significance.

Step-by-step explanation:

Previous concepts

A chi-square goodness of fit test "determines if a sample data matches a population".

A chi-square test for independence "compares two variables in a contingency table to see if they are related. In a more general sense, it tests to see whether distributions of categorical variables differ from each another".

Solution to the problem

Assume the following dataset:

Size Company/ Heal. Ins. Yes No Total

Small 32 18 50

Medium 68 7 75

Large 89 11 100

_____________________________________

Total 189 36 225

We need to conduct a chi square test in order to check the following hypothesis:

H0: independence between heath insurance coverage and size of the company

H1: NO independence between heath insurance coverage and size of the company

The statistic to check the hypothesis is given by:

$\sum_{i=1}^n \frac{(O_i -E_i)^2}{E_i}$

The table given represent the observed values, we just need to calculate the expected values with the following formula $E_i = \frac{total col * total row}{grand total}$

And the calculations are given by:

$E_{1} =\frac{50*189}{225}=42$

$E_{2} =\frac{50*36}{225}=8$

$E_{3} =\frac{75*189}{225}=63$

$E_{4} =\frac{75*36}{225}=12$

$E_{5} =\frac{100*189}{225}=84$

$E_{6} =\frac{100*36}{225}=16$

And the expected values are given by:

Size Company/ Heal. Ins. Yes No Total

Small 42 8 50

Medium 63 12 75

Large 84 16 100

_____________________________________

Total 189 36 225

And now we can calculate the statistic:

$\chi^2 = \frac{(32-42)^2}{42}+\frac{(18-8)^2}{8}+\frac{(68-63)^2}{63}+\frac{(7-12)^2}{12}+\frac{(89-84)^2}{84}+\frac{(11-16)^2}{16}=19.221$

Now we can calculate the degrees of freedom for the statistic given by:

$df=(rows-1)(cols-1)=(3-1)(2-1)=2$

And we can calculate the p value given by:

$p_v = P(\chi^2_{2} >19.221)=0.000067$

And we can find the p value using the following excel code:

"=1-CHISQ.DIST(19.221,2,TRUE)"

Since the p values is higher than a significance level for example $\alpha=0.05$ , we can reject the null hypothesis at 5% of significance, and we can conclude that the two variables are dependent at 5% of significance.

3 0

4 years ago

1 point

Hatshy [7]

Answer:18

Step-by-step explanation:

5 0

3 years ago

What is the measure of angle AFR?

Vladimir [108]

Answer:

Step-by-step explanation:

AFR = VFN (opposite angle rule)

7x + 33 = 9x + 7

33 - 7 = 9x - 7x

26 = 2x

x = 26 : 2

x = 13°

-----------------

check

7 * 13 + 33 = 9 * 13 + 7 (remember PEMDAS)

91 + 33 = 117 + 7

124 = 124

the answer is good

8 0

2 years ago