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Lyrx [107]
1 year ago
11

The Scatter plot below shows the linear trend of the number of golf carts a company sold the month of February and a line of bes

t fit representing this trend.
IT IS A DIFFERENT QUESTION FROM REPAIRING GOLF CARTS PLEASE READ


A. Write a function that models the number of golf carts sold as a function of the number of days in the month of February

B. What is the meaning of the slope as a rate of change for this line of best fit.

Mathematics
1 answer:
Andrei [34K]1 year ago
4 0

Answer:

Part A) y=-5.625x+90

Part B) see the explanation

Step-by-step explanation:

Part A) Write a function that models the number of golf carts sold as a function of the number of days in the month of February

Let

x ----> the number of days

y ----> the number of golf carts sold

we know that

The linear equation in slope intercept form is equal to

y=mx+b

where

m is the slope or unit rate

b is the y-intercept or initial value

In this problem

The y-intercept is the point (0,90)

so

b=90

Find the slope m

The formula to calculate the slope between two points is equal to

m=\frac{y2-y1}{x2-x1}

take two points from the graph

(0,90) and (16,0)

substitute the values in the formula

m=\frac{0-90}{16-0}

m=\frac{-90}{16}

simplify

m=-\frac{45}{8}  ---> is negative because is a decreasing function

therefore

The linear equation is equal to

y=-\frac{45}{8}x+90

Part B) What is the meaning of the slope as a rate of change for this line of best fit

The slope is m=-\frac{45}{8}\ golf\ carts\ sold/days

That means ----> every 8 days 45 less cars are sold

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Answer:

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And rounded up we have that n=1068

Step-by-step explanation:

We have the following info given:

Confidence= 0.95 the confidence level desired

ME =0.03 represent the margin of error desired

The margin of error for the proportion interval is given by this formula:  

ME=z_{\alpha/2}\sqrt{\frac{\hat p (1-\hat p)}{n}}    (a)  

The confidence level is 95% or 0.95, the significance is \alpha=0.05 and the critical value for this case using the normal standard distribution would be z_{\alpha/2}=1.96

Since we don't have prior information we can use \hat p= 0.5 as an unbiased estimator

Also we know that ME =\pm 0.03 and we are interested in order to find the value of n, if we solve n from equation (a) we got:  

n=\frac{\hat p (1-\hat p)}{(\frac{ME}{z})^2}   (b)  

And replacing into equation (b) the values from part a we got:

n=\frac{0.5(1-0.5)}{(\frac{0.03}{1.96})^2}=1067.11  

And rounded up we have that n=1068

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Which of the lines that appear in the graph would be parallel to a line with a slope of 3 and a y-intercept at (0, 3)?
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Step-by-step explanation:

CD is the answer

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2 years ago
Judy’s measured potassium level varies according to the Normal distribution with μ = 3.8 and σ = 0.2 mmol/l. Let us consider wha
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Answer:

The blood potassium level L such that the probability is only 0.05 that the average of four measurements is less than L is 3.64.

Step-by-step explanation:

To solve this question, we have to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

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The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean \mu and standard deviation \sigma, the sample means of size n can be approximated to a normal distribution with mean \mu and standard deviation, which is also called standard error s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 3.8, \sigma = 0.2, n = 4, s = \frac{0.2}{\sqrt{4}} = 0.1

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Z = \frac{X - \mu}{\sigma}

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X = 3.64

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