The purpose of statistical inference population based upon information obtained from the sample.
<h3>What is statistical inference?</h3>
statistical inference uses sample data to make estimates of or draw conclusions about one or more characteristics of a population.
The purpose of statistical inference is to estimate this sample to sample variation or uncertainty. Understanding how much our results may differ if we did the study again, or how uncertain our findings are, allows us to take this uncertainty into account when drawing conclusions. It allows us to provide a plausible range of values for the true value of something in the population, such as the mean, or size of an effect, and it allows us to make statements about whether our study provides evidence to reject a hypothesis.
We have four ideas for using the statistical inference.
1. Estimating uncertainty.
2. Confidence intervals.
3. Hypothesis tests.
4. Connections with other material.
To learn more about statistical inference from the given link:
brainly.com/question/20038845
The given question is not complete.
The purpose of statistical inference is to make estimates or draw conclusions about a population based upon information obtained from the sample.
#SPJ4
The commutative pooperty of x + 7 is equal to 7 + x.
Answer:
−(3x−2)(7x+4)
Step-by-step explanation:
Answer:
97.75 %
Step-by-step explanation:
You score 1 standard deviation above the mean
a) we have from left tail up to the mean 50 % of all values
b) We have in the interval [ μ - σ ; μ + σ ] 95.5 % of all possible values, if we divide that 95.5 by 2 we get 47.75 %, the part of the values that correspond to the right, then in order to get the % of students scored lower we add
50 + 47.75 = 97.75 %
So you can say that the porcentage of students that scored lower than you is 97.75 %
