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3 years ago

These values are standardized test scores. What is the mean score to the nearest tenth?

Mathematics

2 answers:

yarga [219]3 years ago

8 0

If you are speaking in numerical values, it is 29.1. If this is a value of money, it would become $29.10.

kirza4 [7]3 years ago

5 0

First add up the numbers.
27.2+13.5+42.1+37.9+25=145.7
Now divide it by 5
29.14 or 29.1 rounded is the answer

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10w + 4w = -84 solve by combining like terms show all steps leading to awnser plz

Ira Lisetskai [31]

10w + 4w = - 84
14w = - 84
w = - 84 : 14
w = - 6 ( answer )
-----------------------------------
10 * (- 6) + 4 * (- 6) = - 84
- 60 + (- 24) = - 84
- 84 = - 84

3 0

3 years ago

Simplify 1)5x+3=x+13 2)5/2x-1/X =1/6

Artyom0805 [142]

Step-by-step explanation (Question 1):

Step 1: (Question 1): Subtract x from both sides.

5x+3=x+13

5x+3−x=x+13−x

4x+3=13

Step 2: (Question 1): Subtract 3 from both sides.

4x+3−3=13−3

4x=10

Step 3: (Question 1): Divide both sides by 4.

4x/4 = 10/4

FIRST ANSWER: x = 5/2

Step-by-step explanation (Question 2):

Step 1: (Question 2): Multiply by LCM

15x^2 - 6 = x

Step 2: (Question 2): Solve 15x^2

15x^2 - 6 = x:

x = 2/3

x = -3/5

Step 3: (Question 2): Solve

ANSWER: x=0.666667 or x=−0.6

See Attachment 1 for question 1 steps (FULL)

See Attachment 2 for question 2 steps (FULL)

Answer:

1) x = 5/2

2) x=0.666667 or x=−0.6

Hope this helps.

8 0

2 years ago

Read 2 more answers

shi x, miao w, and tchetgen tchetgen ej. (2020). multiply robust causal inference with double negative control adjustment for ca

fomenos

Reliable causal inference based on observational studies is seriously threatened by unmeasured confounding.

What is unmeasured cofounding?

By definition, an unmeasured confounder is a variable that is connected to both the exposed and the result and could explain the apparent observed link.
The validity of interpretation in observational studies is threatened by unmeasured confounding. The use of negative control group to reduce unmeasured confounding has grown in acceptance and popularity in recent years.

Although they've been utilised mostly for bias detection, negative controls have a long history in laboratory sciences and epidemiology of ruling out non-causal causes. A pair of negative control exposure and outcome variables can be utilised to non-parametrically determine the average treatment effect (ATE) from observational data that is vulnerable to uncontrolled confounding, according to a recent study by Miao and colleagues.

Reliable causal inference based on observational studies is seriously threatened by unmeasured confounding.

Learn more about unmeasured confounding here:

brainly.com/question/10863424

#SPJ4

5 0

1 year ago

1. Gerald is an event photographer. In his

Effectus [21]

The information is really hard to follow, you should ask the question with a screenshot of the data table.

6 0

3 years ago

I have 10 apples, I give away 2, how many apples do I have left