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saw5 [17]
2 years ago
7

Nikhil gets paid a 5 percent commission on every pair of shoes that he sells. He earned $1.00 on the last pair of shoes that he

sold. The expression that can be used to represent x, the price of the shoes, is 0.05x = 1 What was the price of the shoes?
Mathematics
2 answers:
Jlenok [28]2 years ago
7 0
If $1 is 5%, 100% would be $1 times 100/5= $1 times 20 = $20
kherson [118]2 years ago
4 0

Answer:

The price of the shoes is $20.

Step-by-step explanation:

Consider the provided information.

Nikhil gets paid a 5 percent commission on every pair of shoes that he sells. He earned $1.00 on the last pair of shoes that he sold.

The expression that can be used to represent x, the price of the shoes, is 0.05x = 1

Now divide both the side by 0.05.

x=\frac{1}{0.05}

The above equation can be written as:

x=\frac{100}{5}

x=20

Thus, the price of the shoes is $20.

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There are 6 blades on each windmill how many total blades are on 7 vwindmills? use fives facts to solves
aliina [53]
6 times 7 = 42      hope helped

8 0
2 years ago
The heights of 1000 students are approximately normally distributed with a mean of 174.5 centimeters and a standard deviation of
yuradex [85]
A. The mean and standard deviation.

The mean of a sampling distribution is approximately equal to the mean of the population. Given that the mean of the population is equal to 174.5, the mean of the sampling distribution is also this value.

The standard deviation of a sample distribution is equal to,

                u(m) = u/sqrt n

Substituting the known values,

               u(m) = 6.9 / sqrt 25 = 1.38

b. Get the z-score of both items,
         
      z-score = (data point - mean) / standard deviation

 z-score of 172.5
     z-score = (172.5 - 174.5) / 1.38 = -1.49
This translates to 0.068.

z-score of 175.8
   z-score = (175.8 - 174.5) / 1.38 = 0.94
This translates to 0.83. 

The difference between the two z-scores is 0.762. 

 The number of samples with this height is 0.762(200) which is equal to approximately 152.

c. z-score of 172 centimeters
   
    z-score = (172 - 174.5) / 1.38
  
    z-score = -1.81
This translates to 0.03.

The number of people with this height from the sample is (0.03)(200) = 6
8 0
2 years ago
Consider the system of linear equations. x + y = 9.0 0.50 x + 0.20 y = 4.05 Find the values of x and y .
mixas84 [53]

Answer:

x=7.5

y=1.5

Step-by-step explanation:

x + y = 9.0

subtract x from both sides

y=9-x

0.50x + 0.20y= 4.05

0.50 x +0.20(9-x)= 4.05

0.50x+1.8-0.2x= 4.05

combine like terms

0.30x+1.8= 4.05

subtract 1.8 from both sides

0.30x=2.25

divide both sides by 0.3

x=7.5

y=9-x

y=9-7.5

y=1.5

4 0
2 years ago
Which data sets have outliers? Check all that apply.
Alex Ar [27]

Answer:

(B), (D) and (E)

Step-by-step explanation:

An outlier is an observation which is quite different or very far from the rest of the given values of the data set.

(A) The given data set is:

14, 21, 24, 25, 27, 32, 35

Since, in the given data set, the values ranges from 14 to 35 in which no outlier is present, thus this data set does not contain any outlier.

thus, this option is incorrect.

(B) The given data set is:

15, 30, 35, 41, 44, 50, 78

In this data set, 78 is an outlier since it is quite far from the rest of the given data values, thus this option is correct.

(C) The given data set is:

16, 32, 38, 39, 41, 42, 58

In the given data set, there is no outlier present, thus this option is incorrect.

(D) The given data set is:

17, 23, 28, 31, 39, 45, 75

In this data set, 75 is an outlier since it is quite far from the rest of the given data values, thus this option is correct.

(E) The given data set is:

18, 30, 34, 38, 43, 45, 68

In this data set, 68 is an outlier since it is quite far from the rest of the given data values, thus this option is correct.

7 0
2 years ago
Read 2 more answers
A member of a student team playing an interactive marketing game received the fol- lowing computer output when studying the rela
nirvana33 [79]

Answer:

p_v = 2*P(t_{n-2} > |t_{calc}|)= 0.91

So on this case for the significance level assumed \alpha=0.05 we see that p_v >\alpha so then we can conclude that the result is NOT significant. And we don't have enough evidence to reject the null hypothesis.

So on this case is not appropiate say that :"the more we spend on advertising this product, the fewer units we sell" since the slope for this case is not significant.

Step-by-step explanation:

Let's suppose that we have the following linear model:

y= \beta_o +\beta_1 X

Where Y is the dependent variable and X the independent variable. \beta_0 represent the intercept and \beta_1 the slope.  

In order to estimate the coefficients \beta_0 ,\beta_1 we can use least squares procedure.  

If we are interested in analyze if we have a significant relationship between the dependent and the independent variable we can use the following system of hypothesis:

Null Hypothesis: \beta_1 = 0

Alternative hypothesis: \beta_1 \neq 0

Or in other words we want to check is our slope is significant (X have an effect in the Y variable )

In order to conduct this test we are assuming the following conditions:

a) We have linear relationship between Y and X

b) We have the same probability distribution for the variable Y with the same deviation for each value of the independent variable

c) We assume that the Y values are independent and the distribution of Y is normal  

The significance level assumed on this case is \alpha=0.05

The standard error for the slope is given by this formula:

SE_{\beta_1}=\frac{\sqrt{\frac{\sum (y_i -\hat y_i)^2}{n-2}}}{\sqrt{\sum (X_i -\bar X)^2}}

Th degrees of freedom for a linear regression is given by df=n-2 since we need to estimate the value for the slope and the intercept.  

In order to test the hypothesis the statistic is given by:

t=\frac{\hat \beta_1}{SE_{\beta_1}}

The p value on this case would be given by:

p_v = 2*P(t_{n-2} > |t_{calc}|)= 0.91

So on this case for the significance level assumed \alpha=0.05 we see that p_v >\alpha so then we can conclude that the result is NOT significant. And we don't have enough evidence to reject the null hypothesis.

So on this case is not appropiate say that :"the more we spend on advertising this product, the fewer units we sell" since the slope for this case is not significant.

3 0
2 years ago
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