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Veseljchak [2.6K]
3 years ago
10

Helppp pleaseee meeee

Mathematics
1 answer:
Serga [27]3 years ago
5 0

Answer:

9 - 11i

Step-by-step explanation:

(3 - 9i) + (6 - 2i)

= (3 + 6) + (-9i - 2i)

= 9 - 11i

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True or False.<br> 43 = 62
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In many fast food restaurants, there is a strong correlation between a menu item's fat content (measured in grams) and its calor
Kruka [31]

Answer:

1. The slope of the least-squares regressin line is 11.364

2. The intercept of the least-squares regression line is 204.343

3. The residual corresponding to this observation is -10 calories

Step-by-step explanation:

1. In order to calculate the slope of the least-squares regressin line we would have to use the following formula:

slope of the least-squares regressin line=r*sy/sx

Therefore, slope=0.979*324.90/27.99

slope=11.364

2. In order to calculate the intercept of the least-squares regression line we would have to use the following formula:

intercept of the least-squares regression line=ybar - slope*xbar

intercept=662.88 - 11.364*40.35

intercept=204.343

3. In order to calculate the the residual corresponding to this observation we would have to use the following formula:

residual = observed y - predicted y

predicted y=11.364*x + 204.343

if the x value is 7, therefore predicted y=11.364*107 + 204.343

predicted y=1,420

Therefore, residual=1410 calories - 1420 calories

residual=-10 calories

8 0
3 years ago
Quick algebra 1 question for 50 points!
snow_tiger [21]

Answer:

Yes.

Step-by-step explanation:

Yes, the given line can be used to make reasonable predictions of the number of cheese pizzas that will be sold, since the scatter points clearly show a trend.

As time goes on, the number of pizzas sold is getting bigger, and the trend is what created the line.

The data was taken over 8 consecutive weeks, so we can assume that it can be used in our prediction.

Since the trend has been pretty consistent over periods of time, we can expect it to continue in the upcoming weeks.

3 0
2 years ago
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