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melomori [17]
3 years ago
6

A student union cafeteria worker checked the weight of ten half-pound bags of whole bean coffee and recorded the following weigh

ts in pounds: 0.48, 0.51, 0.47, 0.49, 0.49, 0.50, 0.52, 0.48, 0.49, 0.51. What is the standard deviation of the weight of these coffee bags?
Mathematics
1 answer:
Likurg_2 [28]3 years ago
7 0

Answer: σ = 0.0154

Step-by-step explanation:

1. Calculate the mean for the recorded data.

(0.48 + 0.51 + 0.47 + 0.49 + 0.49 + 0.50 + 0.52 + 0.48 + 0.49 + 0.51)/10 =

4.94 / 10 = 0.49

The mean is represented with the greek letter μ, so μ = 0.49

2. For each element in the serie, subtract the mean (0.49) and square the result

(0.48 - 0.49)^2 = (-0.01)^2 = 0.0001

(0.51 - 0.49)^2 = (0.02)^2 = 0.0004

(0.47 - 0.49)^2 = (-0.02)^2 = 0.0004

(0.49 - 0.49)^2 = 0

(0.49 - 0.49)^2 = 0

(0.50 - 0.49)^2 = (0.01)^2 = 0.0001

(0.52 - 0.49)^2 = (0.03)^2 = 0.0009

(0.48 - 0.49)^2 = (-0.01)^2 = 0.0001

(0.49 - 0.49)^2 = 0

(0.51 - 0.49)^2 = (0.02)^2 = 0.0004

So we get these results: 0.0001, 0.0004, 0.0004, 0, 0, 0.0001, 0.0009, 0.0001, 0, 0.0004

3. Now, we calculate the mean of these squared differences

(0.0001 + 0.0004 + 0.0004 + 0 + 0 + 0.0001 + 0.0009 + 0.0001 + 0 + 0.0004) / 10 =

(0.0024) / 10 = 0.00024

4. Now to get the standard deviation, we need to get the root of this last value (0.00024).

√(0.00024) = 0.0154

5. So that will be our standard deviation value:

σ = 0.0154

DONE!

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y=-2.95836 x +234.56159

Step-by-step explanation:

We assume that th data is this one:

x: 50, 55, 50, 79, 44, 37, 70, 45, 49

y: 152, 48, 22, 35, 43, 171, 13, 185, 25

a) Compute the equation of the least-squares regression line. (Round your numerical values to five decimal places.)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}

So we can find the sums like this:

\sum_{i=1}^n x_i =50+ 55+ 50+ 79+ 44+ 37+ 70+ 45+ 49=479

\sum_{i=1}^n y_i =152+ 48+ 22+ 35+ 43+ 171+ 13+ 185+ 25=694

\sum_{i=1}^n x^2_i =50^2 + 55^2 + 50^2 + 79^2 + 44^2 + 37^2 + 70^2 + 45^2 + 49^2=26897

\sum_{i=1}^n y^2_i =152^2 + 48^2 + 22^2 + 35^2 + 43^2 + 171^2 + 13^2 + 185^2 + 25^2=93226

\sum_{i=1}^n x_i y_i =50*152+ 55*48+ 50*22+ 79*35+ 44*43+ 37*171+ 70*13+ 45*185+ 49*25=32784

With these we can find the sums:

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=26897-\frac{479^2}{9}=1403.556

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}=32784-\frac{479*694}{9}=-4152.22

And the slope would be:

m=-\frac{-4152.222}{1403.556}=-2.95836

Nowe we can find the means for x and y like this:

\bar x= \frac{\sum x_i}{n}=\frac{479}{9}=53.222

\bar y= \frac{\sum y_i}{n}=\frac{694}{9}=77.111

And we can find the intercept using this:

b=\bar y -m \bar x=77.1111111-(-2.95836*53.22222222)=234.56159

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