M = (x₁ + x₂)/2 , (y₁ + y₂)/2
(-1, 2) = 
At this point, it is easier to separate the x's and y's into two different equations:
x's: -1 =
-2 = 3 + x
-5 = x
y's: 2 = 
4 = 4 + x
0 = x
Answer: (-5, 0)
Answer:
Sample mean from population A has probably more accurate estimate of its population mean than the sample mean from population B.
Step-by-step explanation:
To yield a more accurate estimate of the population mean, margin of error should be minimized.
margin of error (ME) of the mean can be calculated using the formula
ME=
where
- z is the corresponding statistic in the given confidence level(z-score or t-score)
- s is the standard deviation of the sample (or of the population if it is known)
for a given confidence level, and the same standard deviation, as the sample size increases, margin of error decreases.
Thus, random sample of 50 people from population A, has smaller margin of error than the sample of 20 people from population B.
Therefore, sample mean from population A has probably more accurate estimate of its population mean than the sample mean from population B.
Answer:
16 m
Step-by-step explanation:
c=f×m
331=20m ( divide by 20 both side)
therefore m=16.55m
Answer:
<h3>-700</h3>
Step-by-step explanation:

Answer:
<u>direction</u>
<u>shape</u>
<u>scatter plots</u>
<u>shape and outliers</u>
Step-by-step explanation:
Correlation is defined as the degree of correspondence between two variables.
When the values increase together, correlation is positive and when one value decreases as the other increases, correlation is negative .
Calculating a correlation can help describe a relation between two quantitative variables' <u>direction</u> and <u>shape</u>. However, it is not sufficient to use a correlation coefficient to describe two variables. The addition of <u>scatter plots</u> can provide other helpful details such as <u>shape and outliers</u>