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3 years ago

10

Leroy owns a business earning $49,300 in profits, these profits are appreciating at about 2.9% each year. What are leroys profit

s after nine years ?

1 answer:

evablogger [386]3 years ago

7 0

Answer:

$62,167.3

Step-by-step explanation:

Profit after nine years is the amount.

Amount = Principal + Interest

Given

Earning profit = Principal = $49,300

Rate = 2.9%

Time = 9 years

Interest = Principal * Rate * Time/100

Interest = $49,300*2.9*9/100

Interest = 1,286,730/100

Interest = $12,867.30

Amount = $49,300+$12,867.30

Amount = $62,167.3

Hence leroys profits after nine years is $62,167.3

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In the figure above, PQRS is a circle. If PQT and SRT<br>are straight lines, find the value of x.

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Given:

PQRS is a circle, PQT and SRT are straight lines.

To find:

The value of x.

Solution:

Since PQRS is a circle, PQT and SRT are straight lines, therefore, PQRS isa cyclic quadrilateral.

We know that, sum of opposite angles of a cyclic quadrilateral is 180 degrees.

$m\angle SPQ+m\angle QRS=180^\circ$

$81^\circ+m\angle QRS=180^\circ$

$m\angle QRS=180^\circ-81^\circ$

$m\angle QRS=99^\circ$

Now, SRT is a straight line.

$m\angle QRT+m\angle QRS=180^\circ$ (Linear pair)

$m\angle QRT+99^\circ=180^\circ$

$m\angle QRT=180^\circ-99^\circ$

$m\angle QRT=81^\circ$ ...(i)

According to the Exterior angle theorem, in a triangle the measure of an exterior angle is equal the sum of the opposite interior angles.

Using exterior angle theorem in triangle QRT, we get

$m\angle PQR=m\angle QRT+m\angle QTR$

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In a study relating the degree of warping, in mm, of a copper plate (y) to temperature in °C (x), the following summary statisti

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Answer:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

Step-by-step explanation:

Linear regression is a way "to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables)".

Regression estimates are "used to describe data and to explain the relationship between one dependent variable and one or more independent variables"

The linear model is given by the following equation $Y=mx +b$ , where y is the dependent variable, x the independent variable, m the slope and b the intercept.

For this case we have the following info given:

$\sum_{i=1}^n (x_i -\bar x)^2 =98775$

$\sum_{i=1}^n (y_i -\bar y)^2 =19.4$

$\bar x =26.36$

$\bar y =0.5188$

n= 40 represent the sample size

$\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y) =796.94$

The total sum of squares is given by this formula:

$SST= \sum_{i=1}^n (y_i -\bar y)^2 =19.4$

And from the formulas for a simple regression, we need to calculate the slope for the regression like this:

$m=\frac{\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)}{\sum_{i=1}^n (x_i -\bar x)^2}$

And if we replace the values given we have:

$m=\frac{796.94}{98775}=0.008068$

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$SSR=m* \sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)=0.008068*796.94=6.430$

And we know this equivalence:

$SST= SSR+SSE$

And solving for the sum of squares for the error we have:

$SSE=SST-SSR=19.4-6.430=12.97$

So then we have the final solutions:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

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