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ololo11 [35]
3 years ago
8

10. The sides of a number cube have the numbers 9, 3, 5, 3, 7, and 9. If the

Mathematics
2 answers:
BARSIC [14]3 years ago
8 0

Answer:

1/3

Step-by-step explanation:

You have a 1/3 chance that the cube will land on 9

ddd [48]3 years ago
3 0

Answer:

1/3 or 33.333333333%

Step-by-step explanation:

Two 9's

Six number possible

2/6= 1/3

Probability:

1/3 or 33.33333333%

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jose reads 39 books in 1994, 27 books in 1995, and 35 books in 1996. how many books did he read over 3 years
Afina-wow [57]

Answer:101

Step-by-step explanation:

U just add all the numbers together

5 0
3 years ago
What is the slope of the line that contains the points (4,3) and (2, 7)? A. - 5 B. 2 C. -2 O D. -5​
Sindrei [870]

Answer:

C. -2

Step-by-step explanation:

hope that helps! :)

7 0
3 years ago
In a simple regression analysis (where y is a dependent and x an independent variable), if the y-intercept is positive, then it
Rom4ik [11]

Answer:

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  

On this case the correct answer would be:

E.  none of the above

Since the intercept has no association between the increase/decrease of the dependent variable respect to the independent variable

Step-by-step explanation:

Assuming the following options:

A.  there is a positive correlation between X and Y

B.  there is a negative correlation between X and Y

C.  if X is increased, Y must also increase

D.  if Y is increased, X must also increase

E.  none of the above

If we want a model y = mx +b where m represent the lope and b the intercept

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  

On this case the correct answer would be:

E.  none of the above

Since the intercept has no association between the increase/decrease of the dependent variable respect to the independent variable

3 0
3 years ago
Connecticut families were asked how much they spent weekly on groceries. Using the following data, construct and interpret a 95%
Amanda [17]

Answer:

The 95% confidence interval for the population mean amount spent on groceries by Connecticut families is ($73.20, $280.21).

Step-by-step explanation:

The data for the amount of money spent weekly on groceries is as follows:

S = {210, 23, 350, 112, 27, 175, 275, 50, 95, 450}

<em>n</em> = 10

Compute the sample mean and sample standard deviation:

\bar x =\frac{1}{n}\cdot\sum X=\frac{ 1767 }{ 10 }= 176.7

s= \sqrt{ \frac{ \sum{\left(x_i - \overline{x}\right)^2 }}{n-1} }       = \sqrt{ \frac{ 188448.1 }{ 10 - 1} } \approx 144.702

It is assumed that the data come from a normal distribution.

Since the population standard deviation is not known, use a <em>t</em> confidence interval.

The critical value of <em>t</em> for 95% confidence level and degrees of freedom = n - 1 = 10 - 1 = 9 is:

t_{\alpha/2, (n-1)}=t_{0.05/2, (10-1)}=t_{0.025, 9}=2.262

*Use a <em>t</em>-table.

Compute the 95% confidence interval for the population mean amount spent on groceries by Connecticut families as follows:

CI=\bar x\pm t_{\alpha/2, (n-1)}\cdot\ \frac{s}{\sqrt{n}}

     =176.7\pm 2.262\cdot\ \frac{144.702}{\sqrt{10}}\\\\=176.7\pm 103.5064\\\\=(73.1936, 280.2064)\\\\\approx (73.20, 280.21)

Thus, the 95% confidence interval for the population mean amount spent on groceries by Connecticut families is ($73.20, $280.21).

7 0
3 years ago
Write the equation of the function that<br> can be modeled by this table?
Alika [10]

Answer:

<em>y = 3x + 5</em>

Step-by-step explanation:

y = mx + b (slope-intercept form)

( x_{1} , y_{1} )

( x_{2} , y_{2} )

Slope m = \frac{y_{2} -y_{1} }{x_{2} -x_{1} }

y - y_{1} = m( x - x_{1} )  (point-slope form of linear equation)

~~~~~~~~~~~~~~~

3 0
2 years ago
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