Helen's house is located on a rectangular lot that is 1 1/8 miles by 9/10. Estimate the distance around the lot.

1 answer:

7 0

You round 1 1/8 to 1 and 9/10 to 1 (since you are estimating) and then you add 1+1+1+1, which is 4 because to find perimeter you add the lengths and the widths together.

You might be interested in

A barrel of oil was filled at a constant rate of 7.9 gal/min. The barrel had 12 gallons before filling began.

jenyasd209 [6]

The equation that models this situation is z = 7.9y + 12.

A linear equation is a function that has a single variable raised to the power of 1. An example is x = 4y + 2.

Where:

2 is the constant
x = dependent variable
y = independent variable

From the equation given, 12 would be the constant, the independent variable would be 7.9 and z would be the dependent variable.

z = 7.9y + 12

Here is the complete question: A barrel of oil was filled at a constant rate of 7.9 gal/min. The barrel had 12 gallons before filling began. write an equation in standard form to model the linear situation.

A similar question was answered here: brainly.com/question/2238405

4 0

2 years ago

Consider the following hypothesis test: H0: μ1 - μ2 = 0 Ha: μ1 - μ2 ≠ 0 There are two independent samples taken from the two pop

nlexa [21]

Answer:

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:

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