Answer:
The equation of any straight line, called a linear equation, can be written as: y = mx + b, where m is the slope of the line and b is the y-intercept.
Step-by-step explanation:
The y-intercept of this line is the value of y at the point where the line crosses the y axis.
Answer:
804 feet
Step-by-step explanation:
Given: Dimension of a basketball court is 84 feet by 50 feet.
Considering the shape of basketball court is in rectangle shape.
∴ Finding the perimeter of rectangle to know total number of feet in one round.
Perimeter of rectangle= 
where, l= length
w= width
∴ Perimeter of rectangular court= 
⇒ Perimeter of rectangular court= 
Opening parenthesis
⇒ Perimeter of rectangular court= 
Hence, Brett run 268 feet in one round of warm up.
As given, Brett ran around the court 3 times.
∴ Total number of feet= 
Hence, Brett jog for 804 feet.
Answer:
1. a
2. b (i think)
3. b
4. a
5. d
im not sure bout all this but h ope it helps you
Answer: 120
%
=
1.2
If Maxine is correct, then she spent
1.2
times the hours she did homework than last week.
15
⋅
1.2
=
18.0
=
18
15 hours
⋅
1.2
=
18.0 hours
=
18 hours
This means that Maxine is correct.
HOPE THIS HELPS
Answer:
The probability that the sample mean would differ from the population mean by more than 2.6 mm is 0.0043.
Step-by-step explanation:
According to the Central Limit Theorem if we have a population with mean μ and standard deviation σ and appropriately huge random samples (n > 30) are selected from the population with replacement, then the distribution of the sample means will be approximately normally distributed.
Then, the mean of the distribution of sample mean is given by,

And the standard deviation of the distribution of sample mean is given by,

The information provided is:
<em>μ</em> = 144 mm
<em>σ</em> = 7 mm
<em>n</em> = 50.
Since <em>n</em> = 50 > 30, the Central limit theorem can be applied to approximate the sampling distribution of sample mean.

Compute the probability that the sample mean would differ from the population mean by more than 2.6 mm as follows:


*Use a <em>z</em>-table for the probability.
Thus, the probability that the sample mean would differ from the population mean by more than 2.6 mm is 0.0043.