Recall that a test is statistically significant at a particular significance level if the null hypothesis is rejected when alpha is set at this value. Suppose a medical researcher conducts a statistical test of hypotheses and finds there is statistically significant evidence for the alternative hypothesis at a significance level alpha = 0.05. The researcher may conclude that...a) the test would also be statistically significant at level alpha = 0.01b) the test would also be statistically significant at level alpha = 0.10c) both of the above are trued) none of the above are true

Answers

Answer 1
Answer:

Answer:

The correct option is: b) the test would also be statistically significant at level alpha = 0.10

Step-by-step explanation:

Consider the provided information.

Suppose a medical researcher conducts a statistical test of hypotheses and finds there is statistically significant evidence for the alternative hypothesis at a significance level alpha = 0.05.

It means that the test would be statically significant at level alpha = 0.10

As we know that if alternative hypothesis is true then the value of p must be less than α.

That means if the p-value is less than 0.05 then it must be less than 0.10.

Hence, the correct option is: b) the test would also be statistically significant at level alpha = 0.10


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Answers

Answer:

A

C

D

Step-by-step explanation:

The perimeter of a rectangle is 52 feet. Describe the possible lengths of a side if the area of the rectangle is not to exceed 120 square feet. I need to find the solution set for this.

Answers

Answer:

2x+2y=52

x*y=120

Step-by-step explanation:

Final answer:

The possible lengths of a side of the rectangle are 22, 21, 20, 19, 18, 17, 16 feet.

Explanation:

To find the possible lengths of a side of the rectangle, let's use the formula for the perimeter of a rectangle, which is 2(length + width). We can set up an equation using the given information:

2(length + width) = 52

Dividing both sides by 2, we get:

length + width = 26

Now, to find the possible lengths, we need to consider the area. The formula for the area of a rectangle is length x width. We are given that the area is not to exceed 120 square feet, so we can set up the inequality:

length x width <= 120

Using the relationship length + width = 26, we can substitute length = 26 - width into the inequality:

(26 - width) x width <= 120

Simplifying the inequality, we get:

-width^2 + 26width - 120 <= 0

Now, we can solve this quadratic inequality to find the range of possible widths. Once we have the widths, we can substitute them back into the equation length + width = 26 to find the corresponding lengths.

By solving the quadratic inequality, we find that the possible widths are 4 <= width <= 10. Substituting these widths back into the equation length + width = 26, we get the corresponding lengths:

If width = 4, then length = 22

If width = 5, then length = 21

If width = 6, then length = 20

If width = 7, then length = 19

If width = 8, then length = 18

If width = 9, then length = 17

If width = 10, then length = 16

The possible lengths of a side of the rectangle are {22, 21, 20, 19, 18, 17, 16} feet.

Learn more about rectangle side lengths here:

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The number of text messages sent by 25 13-year-olds over the past month are as follows791 542 671 672 555 582 616 961 639
691 648 967 959 826 573 598 790 954
711 515 649 960 949 802 507
a. Construct the frequency distribution using classes of 500 up to 600, 600 up to 700, etc.
Texts Frequency
500 up to 600
600 up to 700
700 up to 800
800 up to 900
900 up to 1000
Total
b. Construct the relative frequency distribution, the cumulative frequency distribution and the cumulative relative frequency distribution. (Round "Relative Frequency" and "Cumulative Relative Frequency" to 2 decimal places.)
Texts Relative Frequency Cumulative Frequency Cumulative Relative Frequency
500 up to 600
600 up to 700
700 up to 800
800 up to 900
900 up to 1000
c-1. How many of the 13-year-olds sent at least 600 but less than 700 text messages?
c-1. Number of 13-year-olds
Number of 13-year-olds
c-2. How many sent less than 900 text messages?
Number of 13-year-olds
d-1. What percent of the 13-year-olds sent at least 800 but less than 900 text messages? (Round your answer to the nearest whole percent.)
Percent of 13-year-olds %
d-5. What percent of the 13-year-olds sent less than 600 text messages? (Round your answer to the nearest whole percent.)
Percent of 13-year-olds %

Answers

Answer:

7 ; 19 ; 8% ; 28%

Step-by-step explanation:

Given the data:

791 542 671 672 555 582 616 961 639

691 648 967 959 826 573 598 790 954

711 515 649 960 949 802 507

How many of the 13-year-olds sent at least 600 but less than 700 text messages? = 7

c-2. How many sent less than 900 text messages? = (7 + 7 + 3 + 2) = 19

d-1. What percent of the 13-year-olds sent at least 800 but less than 900 text messages? =0.08 × 100 = 8% (from relative frequency)

d-5. What percent of the 13-year-olds sent less than 600 text messages?  0.28 × 100 = 28% (from relative frequency)

Final answer:

By sorting text messages into classes, we can get the frequency distribution. From there, we can determine the relative and cumulative frequencies. Finally, we can examine how many students sent texts within certain ranges and express these as percentages.

Explanation:

To answer this question, let's first classify the amount of text messages sent by each of the 25 13-year-olds into groups or classes of 100. Then we count the frequencies, or how many text messages fall into each class. This helps us construct the frequency distribution.

The classes are: 500-600, 600-700, 700-800, 800-900, and 900-1000.

Next, we calculate the relative frequency by dividing the frequency of each class by the total number of students. We round each relative frequency to 2 decimal places.

To calculate cumulative frequency, we keep an ongoing total of frequencies as we move up the classes. The cumulative relative frequency is computed similarly but applied to the relative frequencies.

In the last part, we determine how many 13-year-olds sent at least a certain number of texts but less than another number, and convert these to percentages.

Learn more about Frequency Distribution here:

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Select the correct answer from each drop-down menu. The table shows the heights of the 10 tallest buildings in San Francisco and Los Angeles.

The average height of the 10 tallest buildings in Los Angeles is than the average height of the tallest buildings in San Francisco. The mean absolute deviation for the 10 tallest buildings in San Francisco is

The answer:

Answers

Answer with explanation:

\text{Average}=\frac{\text{Sum of all the observation}}{\text{Total number of Observation}}

Average Height of tallest Building in San Francisco

                    =(260+237+212+197+184+183+183+175+174+173)/(10)\n\n=(1978)/(10)\n\n=197.8

Average Height of tallest Building in Los Angeles

                    =(310+262+229+228+224+221+220+219+213+213)/(10)\n\n=(2339)/(10)\n\n=233.9

→→Difference between Height of tallest Building in Los Angeles and  Height of tallest Building in San Francisco

               =233.9-197.8

               =36.1

⇒The average height of the 10 tallest buildings in Los Angeles is 36.1 more than the average height of the tallest buildings in San Francisco.

⇒Part B

Mean absolute deviation for the 10 tallest buildings in San Francisco

 |260-197.8|=62.2

 |237-197.8|=39.2

 |212-197.8|=14.2

 |197 -197.8|= 0.8

 |184 -197.8|=13.8

 |183-197.8|=14.8

 |183-197.8|= 14.8

 |175-197.8|=22.8

 |174-197.8|=23.8

 |173 -197.8|=24.8

Average of these numbers

     =(62.2+39.2+14.2+0.8+13.8+14.8+14.8+22.8+23.8+24.8)/(10)\n\n=(231.2)/(10)\n\n=23.12

Mean absolute deviation=23.12

Answer:

1st -36.1 meters or more

2nd -23.12

Step-by-step explanation:

The height distribution of NBA players follows a normal distribution with a mean of 79 inches and standard deviation of 3.5 inches. What would be the sampling distribution of the mean height of a random sample of 16 NBA players?

Answers

Answer:

The probability will be "0.0111".

Step-by-step explanation:

The given values are:

Mean,

\mu = 79

Standard deviation,

\sigma = 3.5

Now,

\sigma\bar x = (\sigma)/(\sqrt n)

         =   (3.5)/(\sqrt 16)

         =0.875

P(\bar x > 81) = 1 - P(\bar x < 81)

So,

= 1 - P{((\bar x - \mu \bar x ))/( \sigma \bar x)  < ((81 - 79) )/(0.875) ]

= 1 - P(z < 2.2857)

= 0.0111

Solve for c. a (c+b)=d

Answers

Answer:

c =  (d)/(a) -  b

Step-by-step explanation:

a( c + b ) = d

Divide both sides by a

That's

(a(c + b))/(a)  =  (d)/(a)  \n c + b =  (d)/(a)

Move b to the right side of the equation to make c stand alone

We have the final answer as

c =  (d)/(a) -  b

Hope this helps you

Answer:

c = (d)/(a) - b.

Step-by-step explanation:

a(c + b) = d

(c + b) = d / a

c + b = (d)/(a)

c = (d)/(a) - b.

Hope this helps!