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3 years ago

Find the slope of the line that passes through each pair of points. C(0, –2), D(3, -2)

Mathematics

1 answer:

zaharov [31]3 years ago

5 0

Answer:

Step-by-step explanation:

y2-y1/x2-x1

-2+2/3-0

0/3

= 0

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Simplify the expression below as much as possible. (8 + 5i) + (10 +6i) - (3 +61)

yarga [219]

Answer is -46+11i
Because

Remove unnecessary parenthese
Then

When there is a in front of an expression in parentheses, the expression remains the same

Then

Add the numbers

Calculate the sum or difference

Collect like terms

6 0

3 years ago

Here are the heights in inches of 10 professional basketball players: 66, 74, 76, 77, 78, 79, 80, 80, 82, 84. The mean of these

Dvinal [7]

Answer:

Question 4: The set has 66 as an outlier and removing it increases the mean by about 1.3 inches.

Question 5: The set has 50 as an outlier and removing it increases the mean by about 3.

Step-by-step explanation:

Question 4:

Given heights are:

66, 74, 76, 77, 78, 79, 80, 80, 82, 84

The mean is: 77.6 inches

Removing 66 will make the mean increase to 78.9

So,

The set has 66 as an outlier and removing it increases the mean by about 1.3 inches.

Question 5:

50, 74, 76, 77, 78, 79, 80, 80, 82, 84

The mean is 76.

We can clearly see that 50 is an outlier as it is quite less than the given data.

Calculating mean after removing 50 will give us mean equal to 78.9

So the correct answer is:

The set has 50 as an outlier and removing it increases the mean by about 3.

5 0

3 years ago

Graph the line that passes through the points (-1,-4) and (-2,-1) and

Oksanka [162]

Im dislexic im sorry

7 0

3 years ago

Taci makes birthday cards using sheet of paper for each card. How many cards can she make using 12 sheets of paper?

Zepler [3.9K]

Answer is probably 12
It’s 12 because Taci is using A SHEET OF PAPER for each card. So yea... I’m impressive ik

7 0

3 years ago

Read 2 more answers

.For small training sets variance may contribute more to the overall error than bias. Sometimes this is handled by reducing the

Ymorist [56]

Answer:

Bias is the difference between the average prediction of our model and the correct value which we are trying to predict and variance is the variability of model prediction for a given data p[oint or a value which tells us the spread of our data the variance perform very well on training data but has high error rates on test data on the other hand if our model has small training sets then it's going to have smaller variance & & high bias and its contribute more to the overall error than bias. If our model is too simple and has very few parameters then it may have high bias and low variable. As the model go this is conceptually trivial and is much simpler than what people commonly envision when they think of modelling but it helps us to clearly illustrate the difference bewteen bias & variance.

3 0

3 years ago