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FinnZ [79.3K]
1 year ago
6

A recent study found that 51 children who watched a commercial for Walker Crisps (potato chips) featuring a long-standing sports

celebrity endorser ate a mean of 36 grams of Walker Crisps as compared to a mean of 25 g of Walker Crisps for 41 children who watched a commercial for an alternative food snack. Suppose that the sample standard deviation for the children who watched the sports celebrity–endorsed Walker Crisps commercial was 21.4 g and the sample standard deviation for the children who watched the alternative food snack commercial was 12.8 g. Assuming the population variances are not equal and alpha-05, is there any evidence that the mean amount of Walker Crisps eaten was significantly higher for the children who watched the sports celebrity- endorsed Walker Crisps commercial?
1. What is the claim from the question? What are Null and Alternative Hypothesis for this problem?
2. What kind of test do you want to use?
3. Calculate Test Statistics.
4. Find P-value.
5. What is the conclusion that you could make?
Mathematics
1 answer:
hichkok12 [17]1 year ago
5 0

Answer:

1

The claim is that the mean amount of Walker Crisps eaten was significantly higher for the children who watched the sports celebrity- endorsed Walker Crisps commercial

2

The kind of test to use is a t -test because a t -test is used to check if there is a difference between means of a population

3

t  =  3.054

4

The p-value  is   p-value  =  P(Z >  3.054) = 0.0011291

5

The conclusion is  

There is sufficient evidence to conclude that the mean amount of Walker Crisps eaten was significantly higher for the children who watched the sports celebrity- endorsed Walker Crisps commercial

The test statistics is  

Step-by-step explanation:

From the question we are told that

   The first sample size is  n_1  =  51

    The first sample  mean is \mu_1  =  36

    The second sample size is  n_2  =  41

    The second sample  size is  \mu_2  =  25

     The first standard deviation is  \sigma _1  =  21.4 \  g

    The second standard deviation is  \sigma _2  =  12.8 \  g

  The  level of significance is  \alpha =  0.05

The  null hypothesis is  H_o  :  \mu_1 = \mu_ 2

The  alternative hypothesis is  H_a :  \mu_1 > \mu_2

Generally the test statistics is mathematically represented as

    t  =  \frac{\= x_1 - \= x_2}{ \sqrt{ \frac{s_1^2}{n_1}  + \frac{s_2^2}{n_2}  } }

=>   t  =  \frac{ 36 - 25}{ \sqrt{ \frac{ 21.4^2}{51}  + \frac{ 12.8^2}{41}  } }

=> t  =  3.054

The  p-value is mathematically represented as

     p-value  =  P(Z >  3.054)

Generally from the z table  

             P(Z >  3.054) =  0.0011291

=>   p-value  =  P(Z >  3.054) = 0.0011291

From the values obtained  we see that p-value  < \alpha so  the null hypothesis is rejected

Thus the conclusion is  

  There is sufficient evidence to conclude that the mean amount of Walker Crisps eaten was significantly higher for the children who watched the sports celebrity- endorsed Walker Crisps commercial

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Two rectangular properties share a common side. Lot A is 33 feet wide and 42 feet long.
s344n2d4d5 [400]

Answer:

The width of lot B is 11 feet, so option A is correct.

Step-by-step explanation:

Given:

  • Two rectangular properties share a common side.  
  • Lot A is 33 feet wide and 42 feet long.  
  • The combined area of the lots = 1,848 square feet.  

To find:

How many feet wide is Lot B?  

Solution:

we know that, area of a rectangle is length x breadth

Then area of lot A = 33 x 42 = 1386 square feet.

And area of lot B = width x 42

Now, we are given that, total area = 1848  

area of lot A + area of lot B = 1848  

1386 + width x 42 = 1848  

width x 42 = 1848 – 1386  

width x 42 = 462  

width =\frac{42}{462}

width = 11

Hence, the width of lot B is 11 feet, so option A is correct.

7 0
2 years ago
The quality control manager at a light bulb factory needs to estimate the mean life of a batch (population) of light bulbs. We a
Nadusha1986 [10]

Answer:

<em>a)95%  confidence intervals for the population mean of light bulbs in this batch</em>

(325.5 ,374.5)

b)

<em>The calculated value Z = 4 > 1.96 at 0.05 level of significance</em>

<em>Null hypothesis is rejected </em>

<em>The manufacturer has not right to take the average life of the light bulbs is 400 hours.</em>

Step-by-step explanation:

Given sample size n = 64

Given  mean of the sample x⁻ = 350

Standard deviation of the Population σ = 100 hours

The tabulated value Z₀.₉₅ = 1.96

<em>95%  confidence intervals for the population mean of light bulbs in this batch</em>

<em></em>(x^{-} - Z_{\frac{\alpha }{2} } \frac{S.D}{\sqrt{n} } , x^{-} + Z_{\frac{\alpha }{2} }\frac{S.D}{\sqrt{n} } )<em></em>

<em></em>(350 - 1.96\frac{100}{\sqrt{64} } , 350 + 1.96\frac{100}{\sqrt{64} } )<em></em>

(350 -24.5, 350 +24.5)

(325.5 ,374.5)

b)

<u><em>Explanation</em></u>:-

Given mean of the Population μ = 400

Given sample size n = 64

Given  mean of the sample x⁻ = 350

Standard deviation of the Population σ = 100 hours

<u><em>Null hypothesis</em></u> : H₀:The manufacturer has right to take the average life of the light bulbs is 400 hours.

μ = 400

<u><em>Alternative Hypothesis: H₁:</em></u> μ ≠400

<u><em>The test statistic </em></u>

Z = \frac{x^{-}-mean }{\frac{S.D}{\sqrt{n} } }

Z = \frac{350 -400}{\frac{100}{\sqrt{64} } }

|Z| = |-4|

The tabulated value   Z₀.₉₅ = 1.96

The calculated value Z = 4 > 1.96 at 0.05 level of significance

Null hypothesis is rejected.

<u><em>Conclusion:</em></u>-

The manufacturer has not right to take the average life of the light bulbs is 400 hours.

5 0
2 years ago
Three highways connect city A with city B. Two highways connect city B with city C.
QveST [7]
(a) The probability that there is no open route from A to B is (0.2)^3 = 0.008.
Therefore the probability that at least one route is open from A to B is given by: 1 - 0.008 = 0.992.
The probability that there is no open route from B to C is (0.2)^2 = 0.04.
Therefore the probability that at least one route is open from B to C is given by:
1 - 0.04 = 0.96.
The probability that at least one route is open from A to C is:
0.992\times0.96=0.9523

(b)
α The probability that at least one route is open from A to B would become 0.9984. The probability in (a) will become:0.9984\times0.96=0.95846

β The probability that at least one route is open from B to C would become 0.992. The probability in (a) will become:
0.992\times0.992=0.9841

Gamma: The probability that a highway between A and C will not be blocked in rush hour is 0.8. We need to find the probability that there is at least one route open from A to C using either a route A to B to C, or the route A to C direct. This is found by using the formula:
P(A\cup B)=P(A)+P(B)-P(A\cap B)
0.9523+0.8-(0.9523\times0.8)=0.99
Therefore building a highway direct from A to C gives the highest probability that there is at least one route open from A to C.


4 0
2 years ago
In the expression " 5.3t - (20÷4) + 11" what part is a quotient? Describe its parts.​
enyata [817]

Answer:

(20 divided by 4) is the quotient

Step-by-step explanation:

4 0
1 year ago
Read 2 more answers
Merrill Lynch Securities and Health Care Retirement Inc. are two large employers in downtown Toledo, Ohio. They are considering
ratelena [41]

Answer:

Step-by-step explanation:

We would determine the mean an standard deviation first

Mean = (107 + 92 + 97 + 95 + 105 + 101 + 91 + 99 + 95 + 104)/10 = 98.6

Standard deviation = √(summation(x - mean)/n

n = 10

Summation(x - mean) = (107 - 98.6)^2 + (92 - 98.6)^2 + (97 - 96.6)^2 + (95 - 98.6)^2 + (105 - 98.6)^2 + (101 - 98.6)^2 + (91 - 98.6)^2 + (99 - 98.6)^2 + (95 - 98.6)^2 + (104 - 98.6)^2 = 274

Standard deviation = √(274/10) = 5.23

The confidence interval is used to determine the range of values that could possibly contain a population parameter (population mean)

Confidence interval is written in the form,

(Point estimate - margin of error, Point estimate + margin of error)

The sample mean, x is the point estimate for the population mean.

We will use the t distribution because the sample size is small and the population standard deviation is not given.

Degree of freedom, df = 10 - 1 = 9

α = 1 - 0.99 = 0.01

z α/2 = 0.01/2 = 0.005

The area to the right of z 0.005 is 0.005 and the area to the left of z0.005 is 1 - 0.005 = 0.995. Using the t distribution table,

z = 3.25

Margin of error = z × s/√n

Where

s = sample standard Deviation = 5.23

Margin of error = 3.25 × 5.23/√10 = 5.38

Confidence interval = sample mean(point estimate) ± z × σ/√n

The lower boundary of the confidence interval is

98.6 - 5.38 = 93.22

The upper boundary of the confidence interval is

98.6 + 5.38 = 103.98

We estimate with 99% confidence that the mean weekly child care cost of their employees is between $93.22 and $103.98

Also,

99% of the confidence intervals constructed in this way would contain the true value for the population mean of mean weekly child care cost of their employees.

6 0
1 year ago
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