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zepelin [54]
3 years ago
13

Robbie, has scored 120 so far this season. He has scored all of his points on 1-point extra point kicks and 3-point field goals.

He has made a total of 66 kicks. How many of each kick has he made?
Mathematics
2 answers:
joja [24]3 years ago
6 0

Answer:

39 and 27

Step-by-step explanation:

GIVEN: Robbie, has scored 120 so far this season. He has scored all of his points on 1-point extra point kicks and 3-point field goals. He has made a total of 66 kicks.

TO FIND: How many of each kick has he made.

SOLUTION:

Lets extra point kicks made by Robbie be x

points scored using extra point kick =1

field goal kicks made by Robbie =66-x

point scored using field goal kick =3

Total points scored by Robbie =120

Total points scored are the sum of points scored by extra point kicks and field goal kicks.

1\times x+(66-x)3=120

198-2x=120

2x=78

x=39

total extra point kicks =39

total field goal kicks =66-39=27

Hence Robbie made 39 and 27 kicks of extra point kick and field goal kicks respectively.

mojhsa [17]3 years ago
6 0

Answer:

39 extra point kicks were made and 27 field goals were made.

Step-by-step explanation:

We are given the following in the question:

Let x be the 1-point extra point kicks and y be the number of field goals.

Total number of kicks = 66

Thus, we can write the equation:

x + y = 66

Total score = 120

Thus, we can write the equation:

x + 3y = 120

Solving the equation, we get,

x + 3y-(x + y) = 120-66\\2y = 54\\\Rightarrow y = 27\\\Rightarrow x = 66-27 = 39

Thus, 39 extra point kicks were made and 27 field goals were made.

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Given Information:

Mean = μ = $282.45

Standard deviation = σ = $64.50

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Required Information:  

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Answer:

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Step-by-step explanation:

We are given a Normal Distribution, which is a continuous probability distribution and is symmetrical around the mean. The shape of this distribution is like a bell curve and most of the data is clustered around the mean. The area under this bell shaped curve represents the probability.

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The confidence interval represents an interval that we can guarantee that the target variable will be within this interval for a given confidence level.  

The confidence interval is given by

CI = \bar{x} \pm MoE\\

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MoE = z_{\alpha/2}(\frac{\sigma}{\sqrt{n} } ) \\

Where σ is the standard deviation, n is the sample size and z_{\alpha/2} is the z-score corresponding to 95% confidence level.

z_{\alpha/2} = 1 - 0.95 = 0.05/2 = 0.025\\\\z_{0.025} = 1.96

MoE = 1.96\cdot \frac{64.50}{\sqrt{100} } \\\\MoE = 1.96\cdot 6.45\\\\MoE = 12.64\\

Finally, the confidence interval is

CI = \bar{x} \pm MoE\\\\CI = 282.45 \pm 12.64\\\\CI = 282.45 - 12.64 \: and \: 282.45 + 12.64\\\\CI = \$269.81 \: and \:\:\$295.09\\

Therefore, we are 95% sure that the true population mean amount spent per day by a family of four visiting Niagara Falls is within the interval of ($269.81, $295.09)

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