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Ede4ka [16]
2 years ago
8

Bob's exam score was 2.17 standard deviations above the mean. the exam was taken by 200 students. assuming a normal distribution

, how many scores were higher than bob's?
Mathematics
2 answers:
maks197457 [2]2 years ago
4 0
Assuming that it is a normal distribution, then at 2 standard deviation 97.7 % belongs to the distribution and at 3 standard deviation 99.9 % belongs to the group. so to calculate the percentage in 2.17 standard deviation.
(2 - 2.17) / ( 2 - 3) = ( 97.7 - x) / ( 97.7 - 99.9 )
solve for x, which represents the percentage in the 2.17 standard deviations
x = 98.07 %
100 - 98.07 = 1.93 % scores were higher than bob's
Lemur [1.5K]2 years ago
3 0

The <em><u>correct answer</u></em> is:

1.5% of the scores, or 3 people.

Explanation:

A z-score tells the number of standard deviations a data point is from the mean. Since Bob's score is 2.17 standard deviations above the mean, that means his z-score is 2.17.

Using a z-table, we find the probability that a score would be to the left of, or less than, this value. In the table, this is 0.9850. However, we are interested in the number of people that scored <em>higher</em> than Bob. This means we subtract this from 1:

1-0.9850 = 0.015.

This is the percentage of people that scored higher than Bob. To convert to a percent, multiply by 100:

0.015*100 = 1.5.

To find the number of people that scored higher than Bob, take 1.5% of 200:

0.015(200) = 3.

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Suppose you roll a pair of honest dice. If you roll a total of 7 you win $22, if you roll a total of 11 you win $66, if you roll
JulijaS [17]

Answer:

The expected payoff for this game is -$1.22.

Step-by-step explanation:

It is given that a pair of honest dice is rolled.

Possible outcomes for a dice = 1,2,3,4,5,6

Two dices are rolled then the total number of outcomes = 6 × 6 = 36.

\{(1,1),(1,2),(1,3),(1,4),(1,5),(1,6),(2,1),(2,2),(2,3),(2,4),(2,5),(2,6),\\(3,1),(3,2),(3,3),(3,4),(3,5),(3,6),(4,1),(4,2),(4,3),(4,4),(4,5),(4,6),\\(5,1),(5,2),(5,3),(5,4),(5,5),(5,6),(6,1),(6,2),(6,3),(6,4),(6,5),(6,6)\}

The possible ways of getting a total of 7,

{ (1,6), (2,5), (3,4), (4,3), (5,2), (6,1) }

Number of favorable outcomes = 7

Formula for probability:

Probability=\frac{\text{Favorable outcomes}}{\text{Total outcomes}}

So, the possibility of getting a total of 7 = \frac{6}{36}=\frac{1}{6}

The possible ways of getting a total of 11,

{(5,6), (6,5)}

So, the probability of getting a total of 11 = \frac{2}{36} = \frac{1}{18}

Now, other possible rolls = 36 - 6 - 2 = 36 - 8 = 28,

So, the probability of getting the sum of numbers other than 7 or 11 = \frac{28}{36} = \frac{7}{9}

Since, for the sum of 7, $ 22 will earn, for the sum of 11, $ 66 will earn while for any other total loss is $11,

Hence, the expected value for this game is

\frac{1}{6}\times 22+\frac{1}{18}\times 66-\frac{7}{9}\times 11

\frac{11}{3}+\frac{11}{3}-\frac{77}{9}

\frac{22}{3}-\frac{77}{9}

\frac{66-77}{9}

-\frac{11}{9}

-1.22

Therefore the expected payoff for this game is -$1.22.

4 0
1 year ago
What is the maximum vertical distance between the line y = x + 56 and the parabola y = x2 for −7 ≤ x ≤ 8?
atroni [7]
-7 and 8 are the solutions to the given equation system.
Therefore, the maximum distance between the y values of the two equations must lie exactly between their points of intersection. That is on x value:
x = (-7 + 8)/2 = 0.5
The maximum distance is:
y = 0.5 + 56 = 56.5
y = 0.5² = 0.25
56.5 - 0.25 = 56.25 units
5 0
1 year ago
A man is 6 feet 2 inches tall. To find the height of a tree, the shadow of the man and the shadow of the tree were measured. The
Readme [11.4K]
Here's my work. Hope it helps.
3 0
2 years ago
Noah fills a soap dispenser from a big bottle that contains 2 13 liters of liquid soap. That amount of soap will fill 3 12 dispe
Harrizon [31]

Answer:

0.68L per dispenser

Step-by-step explanation:

Big bottle contain 213L of soap.

Big bottle will fill 312 dispensers.

This means 1 each dispenser can take 213/312 litres = 0.68L per dispenser.

3 0
2 years ago
Read 2 more answers
To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assig
Keith_Richards [23]

Answer:

1. Null hypothesis: \mu_{A}=\mu_{B}=\mu_{C}

Alternative hypothesis: Not all the means are equal \mu_{i}\neq \mu_{j}, i,j=A,B,C

2. D. 36

3. C. 34

4. B. 1.059

5. B. 8.02

Step-by-step explanation:

Analysis of variance (ANOVA) "is used to analyze the differences among group means in a sample".

The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"

Part 1

The hypothesis for this case are:

Null hypothesis: \mu_{A}=\mu_{B}=\mu_{C}

Alternative hypothesis: Not all the means are equal \mu_{i}\neq \mu_{j}, i,j=A,B,C

Part 2

In order to find the mean square between treatments (MSTR), we need to find first the sum of squares and the degrees of freedom.

If we assume that we have p groups and on each group from j=1,\dots,p we have n_j individuals on each group we can define the following formulas of variation:  

SS_{total}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x)^2

SS_{between}=SS_{model}=\sum_{j=1}^p n_j (\bar x_{j}-\bar x)^2

SS_{within}=SS_{error}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x_j)^2

And we have this property

SST=SS_{between}+SS_{within}

We need to find the mean for each group first and the grand mean.

\bar X =\frac{\sum_{i=1}^n x_i}{n}

If we apply the before formula we can find the mean for each group

\bar X_A = 27, \bar X_B = 24, \bar X_C = 30. And the grand mean \bar X = 27

Now we can find the sum of squares between:

SS_{between}=SS_{model}=\sum_{j=1}^p n_j (\bar x_{j}-\bar x)^2

Each group have a sample size of 4 so then n_j =4

SS_{between}=SS_{model}=4(27-27)^2 +4(24-27)^2 +4(30-27)^2=72

The degrees of freedom for the variation Between is given by df_{between}=k-1=3-1=2, Where  k the number of groups k=3.

Now we can find the mean square between treatments (MSTR) we just need to use this formula:

MSTR=\frac{SS_{between}}{k-1}=\frac{72}{2}=36

D. 36

Part 3

For the mean square within treatments value first we need to find the sum of squares within and the degrees of freedom.

SS_{within}=SS_{error}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x_j)^2

SS_{error}=(20-27)^2 +(30-27)^2 +(25-27)^2 +(33-27)^2 +(22-24)^2 +(26-24)^2 +(20-24)^2 +(28-24)^2 +(40-30)^2 +(30-30)^2 +(28-30)^2 +(22-30)^2 =306

And the degrees of freedom are given by:

df_{within}=N-k =3*4 -3 = 12-3=9. N represent the total number of individuals we have 3 groups each one with a size of 4 individuals. And k the number of groups k=3.

And now we can find the mean square within treatments:

MSE=\frac{SS_{within}}{N-k}=\frac{306}{9}=34

C. 34

Part 4

The test statistic F is given by this formula:

F=\frac{MSTR}{MSE}=\frac{36}{34}=1.059

B. 1.059

Part 5

The critical value is from a F distribution with degrees of freedom in the numerator of 2 and on the denominator of 9 such that we have 0.01 of the area in the distribution on the right.

And we can use excel to find this critical value with this function:

"=F.INV(1-0.01,2,9)"

And we will see that the critical value is F_{crit}=8.02

B. 8.02

5 0
2 years ago
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