R example: 6 1/2 = 13/2 = 6.5

For the first example, six and a half is equal to thirteen halves, which is then equal to six point five. To do this, the rule to turn a mix number into a fraction is by multiplying the 2 with the 6 and then add the answer to 1, which gives 13/2 (Remember to always give the same denominator). Finally, thirteenth halves is equal to six point five (because when you divide 13 by 2, you get 6 and one left over. To continue dividing, add a 0 , and so 10 goes into 2 is five. so the decimal is 6.5

4 0

3 years ago

Sarah went to the candy store to buy treats for her halloween party. She came out with 11 pounds of candy. She bought m&m's

Papessa [141]

Answer:

5lb of m&mns and 6lb of raisinets

Step-by-step explanation:

5lb x 2$ = $10

6lb x 1.5 = $9

8 0

3 years ago

A professor went to a website for rating professors and looked up the quality rating and also the "easiness" of the six full-tim

Marat540 [252]

We are asked to determine the correlation factor "r" of the given table. To do that we will first label the column for "Quality" as "x" and the column for "Easiness" as "y". Like this:

Now, we create another column with the product of "x" and "y". Like this:

Now, we will add another column with the squares of the values of "x". Like this:

Now, we add another column with the squares of the values of "y":

Now, we sum the values on each of the columns:

Now, to get the correlation factor we use the following formula:

$r=\frac{n\Sigma xy-\Sigma x\Sigma y}{\sqrt{(n\Sigma x^2-(\Sigma x)^2)(n\Sigma y^2-(\Sigma y)^2)}}$

Where:

$\begin{gathered} \Sigma xy=\text{ sum of the column of xy} \\ \Sigma x=\text{ sum of the column x} \\ \Sigma y=\text{ sum of the column y} \\ \Sigma x^2=\text{ sum of the column x\textasciicircum2} \\ \Sigma y^2=\text{ sum of the column y\textasciicircum2} \\ n=\text{ number of rows} \end{gathered}$

Now we substitute the values, we get:

$r=\frac{\left(6)(70.56)-(25.2)(16.4\right)}{\sqrt{((6)(107.12)-(25.2)^2)((6)(47.82)-(16.4)^2)}}$

Solving the operations:

$r=0.858$

Therefore, the correlation factor is 0.858. If the correlation factor approaches the values of +1, this means that there is a strong linear correlation between the variables "x" and "y" and this correlation tends to be with a positive slope.

7 0

8 months ago