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Nina [5.8K]
3 years ago
10

Each calendar will sell for 5 each. Write an equation to model the total income, y, for selling x calendars

Mathematics
1 answer:
OleMash [197]3 years ago
3 0

Answer:

y = 5x

Step-by-step explanation:

If each calendar, <em>x</em>,  sells for $5 each, you would multiply 5·x because $5 is how much you earn per calender. Therefore, your total income would be 5 times the number of calendars you sell, or in equation "language", y = 5x

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Find the derivative of Y=2xcos2x​
Nastasia [14]

Answer:

Y' = -xsin(2x) + 2cos(2x)

Step-by-step explanation:

For this problem, we will need to use the product rule since you have two terms that contain the variable x.

The product rule is simply as follows:

The derivative of the function is the product of the first term times the derivative of the second term plus the derivative of the first term times the second term.

Note the derivative of 2x with respect to x, is 2.

Note the derivative of cos(2x) with respect to x is (-1/2) sin(2x).

With this in mind, let's find the derivative of our function with respect to x.

Y = 2xcos2x

Y = 2x * cos(2x)

Y' = 2x * (-1/2)sin(2x) + 2 * cos(2x)

Y' = (2x * -1 / 2) sin(2x) + 2 * cos(2x)

Y' = (-x)sin(2x) + 2cos(2x)

So the derivative of our function is Y' = -xsin(2x) + 2cos(2x) according to the application of the product rule.

Cheers.

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3 years ago
I am a quantity that can change or vary, taking on different values. Who am I?
Zigmanuir [339]
The answer is You are a variable
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Location is known to affect the number, of a particular item, sold by an automobile dealer. Two different locations, A and B, ar
yKpoI14uk [10]

Answer:

We conclude that the true mean number of sales at location A is fewer than the true mean number of sales at location B.

Step-by-step explanation:

We are given that Location A was observed for 18 days and location B was observed for 13 days.  

On average, location A sold 39 of these items with a sample standard deviation of 8 and location B sold 49 of these items with a sample standard deviation of 4.

<em>Let </em>\mu_1<em> = true mean number of sales at location A.</em>

<em />\mu_2 = <em>true mean number of sales at location B</em>

So, Null Hypothesis, H_0 : \mu_1-\mu_2\geq0  or  \mu_1 \geq \mu_2     {means that the true mean number of sales at location A is greater than or equal to the true mean number of sales at location B}

Alternate Hypothesis, H_A : \mu_1-\mu_2  or  \mu_1< \mu_2    {means that the true mean number of sales at location A is fewer than the true mean number of sales at location B}

The test statistics that would be used here <u>Two-sample t test statistics</u> as we don't know about the population standard deviations;

                        T.S. =  \frac{(\bar X_1-\bar X_2)-(\mu_1-\mu_2)}{s_p\sqrt{\frac{1}{n_1}+\frac{1}{n_2}  } }  ~ t_n__1_-_n__2-2

where, \bar X_1 = sample average of items sold at location A = 39

\bar X_2 = sample average of items sold at location B = 49

s_1 = sample standard deviation of items sold at location A = 8

s_2 = sample standard deviation of items sold at location B = 4

n_1 = sample of days location A was observed = 18

n_2 = sample of days location B was observed = 13

Also,  s_p=\sqrt{\frac{(n_1-1)s_1^{2}+(n_2-1)s_2^{2}  }{n_1+n_2-2} }  = \sqrt{\frac{(18-1)\times 8^{2}+(13-1)\times 4^{2}  }{18+13-2} }  = 6.64

So, <u><em>test statistics</em></u>  =  \frac{(39-49)-(0)}{6.64 \times \sqrt{\frac{1}{18}+\frac{1}{13}  } }  ~ t_2_9  

                               =  -4.14

The value of t test statistics is -4.14.

Now, at 0.01 significance level the t table gives critical value of -2.462 at 29 degree of freedom for left-tailed test.

<em>Since our test statistics is less than the critical values of t as -2.462 > -4.14, so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which </em><u><em>we reject our null hypothesis</em></u><em>.</em>

Therefore, we conclude that the true mean number of sales at location A is fewer than the true mean number of sales at location B.

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