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stealth61 [152]
3 years ago
7

Really just free points, should be easy

Mathematics
2 answers:
NARA [144]3 years ago
7 0
15+26s-6=25s-9

26s+9=25s-9

s+9=-9

s=-18


Keith_Richards [23]3 years ago
6 0

Answer:

s = - 18

Step-by-step explanation:

15 + 26s - 6 = - 9 + 25s

9 + 26s = - 9 + 25s

18 = - s

s = - 18

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A toll-free sales line sold 85 products for every 125 calls in one day. What is the daily success rate of the sales line? A. 0.1
IgorLugansk [536]

Answer:

C. 0.68

Step-by-step explanation:

Given;

number of products sold in a day by toll-free sales line = 85 products

number of calls in a day = 125

The daily success rate of the sales line is given by the ratio of the total products in a day to total number of calls in a day.

The daily success rate of the sales line = total products sold / number of calls

The daily success rate of the sales line = 85 / 125

The daily success rate of the sales line = 0.68

Therefore, the daily success rate of the sales line is 0.68

7 0
3 years ago
ANSWER ASAP PLZ
stira [4]
60,000,000

Hope this helps :)
5 0
3 years ago
Read 2 more answers
W + what - s = w <br> help plz help helppp i want help
grandymaker [24]

Answer: S

Step-by-step explanation:

w + ? - s = w

w + s - s = w

w = w

7 0
3 years ago
I need help on 4 &amp; 5 pls
Allushta [10]
What do you need help with? it helps us to know the question!
7 0
3 years ago
Consider the following statements:
Artyom0805 [142]

Answer:

d. Both I and II are false

Step-by-step explanation:

When there is a high degree of linear correlation between the predictors the errors are found.

The basic objective of the regression model is to separate the dependent and independent variables. So if the variables have high degree of linear correlation then the multi collinearity causes problems or has errors. It is not necessary that multi collinearity must be present with high degree of linear correlation.

For example we have 3 variable of heat length and time. And all of them have a high degree of correlation. With increase in heat and time the length increases . But for multi collinearity with the increase of time and decrease of heat length does not increase. So this causes errors.

y-hat = 135 + 6x + errors

The linear relationship between height and weight is inexact. The deterministic relation in such cases is then modified to allow the inexact relationship between variables and a non deterministic or probabilistic model is obtained which has  error which are unknown random errors.

y- hat= a + bXi + ei   (i=1,2,3...)

ei are the unknown random errors.

<u><em>So both statements are false.</em></u>

<em><u /></em>

7 0
3 years ago
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