Question 1. Which of the following is not true for the equation six times d equals twelve?

1 answer:

8 0

Q1. The answer is To solve, you must divide both sides by 6

The equation is: 6d = 12
Multiplication is the inverse operation: TRUE - 6d = 12 d = 12/6
Checking the solution involves multiplication: TRUE - 6 * 2 = 12
The equation represents the number that gives twelve when multiplied by 6: TRUE d is the number that gives twelve when multiplied by 6
To solve, you must divide both sides by 6: false

Q2. The answer is 18

x - the number of students

The students were divided equally among 3 chaperones: 3 chaperones per x
Each chaperone supervised 6 students: 1 chaperone per 6 students

3 : x = 1 : 6
x = 3 * 6 : 1
x = 18

Q3. The answer is t is greater than or equal to five.

It will take Harlon at least five years to complete his college degree. The key word is at least. This means that it can include number 5 as well. He may need 5 years, 6 years, 7 years,... Hence, t is greater than or equal to five.

Q4. The answer is 1.2

p over zero point three + 2 = 6
p/0.3 + 2 = 6

multiply both sides by 0.03
p + 2 * 0.3 = 6 * 0.3
p + 0.6 = 1.8
p = 1.8 - 0.6
p = 1.2

Q5. The answer is 2.

16w = 32

Divide both sides by 16
16w/16 = 32/16
w = 2

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The value of the test statistic is $z = 1.78$

Step-by-step explanation:

Before finding the test statistic, we need to understand the central limit theorem and subtraction of normal variables.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Subtraction between normal variables:

When two normal variables are subtracted, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.

Sample 1:

$\mu_1 = 110, s_1 = \frac{7.2}{\sqrt{81}} = 0.8$