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ipn [44]
3 years ago
11

2. A sweater costs $35. Find the total cost of the sweater if the sales tax is 5%.

Mathematics
2 answers:
Vika [28.1K]3 years ago
5 0
It is $36.75

5% of $35 = $1.75

So our sales tax is $1.75
Now let’s add that onto our original price to find the total cost of this sweater....

$35 + $1.75 = 36.75


:)
Crank3 years ago
3 0

Answer:

It is 36.75$.

Step-by-step explanation:

I just took a test and that question was on there

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Mama L [17]

Answer:

just divide. 729/3 = 243

4 0
3 years ago
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Have a look of the drawing... What is "d" value? I have tried many methods but don't find how to solve... Pleaseeee
Phoenix [80]
I´d say "d" is the distance from the eye to the wall. 
Now substracting 1.2-1 you´ll get the distance of the wall of the smallest triangle = 0.2 And you do 1.5-0.2= 0.3 that´s the distance of the wall of the other triangle. Then you solve everything with Pitagoras theorem. You have 2 rectangle triangles.
B+alfa=45°
tan^-1(0.2/d)=B
tan^-1(1.3/d)=alfa
THEN:
tan^-1(0.2/d)+tan^-1(1.3/d)=45°
 Now you have 3 ecs and 3 variables.
alfa,B and "d"

3 0
3 years ago
Read 2 more answers
Thompson and Thompson is a steel bolts manufacturing company. Their current steel bolts have a mean diameter of 139 millimeters,
FinnZ [79.3K]

Answer:

0.4010 = 40.10% probability that the sample mean would differ from the population mean by more than 0.8 millimeters

Step-by-step explanation:

To solve this question, we need to understan 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:

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

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 with size n of at least 30 can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 139, \sigma = 6, n = 40, s = \frac{6}{\sqrt{40}} = 0.9487

Either the sample mean differs by 0.8 mm or less from the population mean, or it differs by more. The sum of these probabilities is decimal 1.

Probability it differs by less than 0.8mm

pvalue of Z when X = 139 + 0.8 = 139.8mm subtracted by the pvalue of Z when X = 139 - 0.8 = 138.2 mm

X = 139.8

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

By the Central Limit Theorem

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

Z = \frac{139.8 - 139}{0.9487}

Z = 0.84

Z = 0.84 has a pvalue of 0.7995

X = 138.2

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

Z = \frac{138.2 - 139}{0.9487}

Z = -0.84

Z = -0.84 has a pvalue of 0.2005

0.7995 - 0.2005 = 0.5990

What is the probability that the sample mean would differ from the population mean by more than 0.8 millimeters?

p + 0.5990 = 0.4010

0.4010 = 40.10% probability that the sample mean would differ from the population mean by more than 0.8 millimeters

7 0
3 years ago
18 divided by 29 is what pleses answer
DanielleElmas [232]
0.62068966 or 18/29 depending on how you want to set it up.
8 0
2 years ago
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The least-squares regression model y =−3.4+5.2x and correlation coefficient r=−0.66 were calculated for a set of bivariate data
Makovka662 [10]

Answer:

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}  

For this case the value of r = -0.66

Now we can calculate the determination coeffcient:

r^2 = (-0.66)^2 = 0.4356

And then we can conclude that 43.56% of the variation in y can be explained by the explanatory variable

And then 100-43.56 = 56.44 % of the variation in y that cannot be explained by the explanatory variable

Step-by-step explanation:

For this case we need to calculate the slope with the following formula:

m=\frac{S_{xy}}{S_{xx}}

Where:

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}

\bar x= \frac{\sum x_i}{n}

\bar y= \frac{\sum y_i}{n}

And we can find the intercept using this:

b=\bar y -m \bar x

And the model obtained for this case is:

y = -3.4 +5.2 x

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.

And in order to calculate the correlation coefficient we can use this formula:  

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}  

For this case the value of r = -0.66

Now we can calculate the determination coeffcient:

r^2 = (-0.66)^2 = 0.4356

And then we can conclude that 43.56% of the variation in y can be explained by the explanatory variable

And then 100-43.56 = 56.44 % of the variation in y that cannot be explained by the explanatory variable

8 0
2 years ago
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