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inferential statistics

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  • Inferential Statistics

Inferential statistical procedures are used to - answer-make inductive inferences of population parameters using sample statistics Interval estimates quantify - answer-level of uncertainty regarding true value of a parameter why are descriptive statistics necessary - answer-whenever simple qu...

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  • September 3, 2024
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  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • Inferential statistics
  • Inferential statistics
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TOPDOCTOR
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INFERENTIAL STATISTICS EXAMINATIONS
WITH ANSWERS
Inferential statistical procedures are used to - answer-make inductive inferences of
population parameters using sample statistics

Interval estimates quantify - answer-level of uncertainty regarding true value of a
parameter

why are descriptive statistics necessary - answer-whenever simple quantitative
description is required

why are inferential statistics necessary - answer-only when a quantitative inductive
inference about population parameter(s) needs to be made

Using inferential statistics, you are trying to reach a conclusion that - answer-
extends beyond immediate data alone - to make inductive inferences about
population parameters based on probability.

inferential statistics is what type of inference - answer-probabilistically-based
inductive inference

ways we use inferential statistics - answer-estimation and hypothesis testing

types of estimation - answer-point(mean, variance, SD and proportions)

and interval(CI and margin of error)

what is a point estimate - answer-A single value for a sample summary statistic
representing the "best guess" value of a parameter.

a ________ is a point estimate of the ________ which is also called______ - answer-
sample mean
population mean
parameter

The best inference of a population mean is? what about a population SD - answer-a
sample mean.
a sample SD

why is There is always uncertainty about how close a sample statistic is to the
unknown population parameter. - answer-A point estimate, by itself, provides no
information on the degree of uncertainty.

Due to sampling error we can only infer from samples to population parameters.


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Interval estimation is a - answer-range of values around a point estimate that, with
a specified level of certainty or probability, enclose the true parameter.

what does an interval measure - answer-CI and margin of error

what is probability - answer-the chance that an event will happen relative to all
possible events that could happen - under defined conditions.

probability can be used to quantify - answer-quantify how sure (or unsure) one is
about the truth of a proposition or statement.

what is a model - answer-All probability statements are based on a set of
assumptions or conditions

ex-under these conditions, the prob of x is y%

All probabilities are - answer-ratios. It is essential to define both the numerator
(particular event occurs) and denominator (number of all possible events, given
conditions).

what is an interval - answer-a range of values around a point estimate made on a
sample

what is a CI - answer-a quantitative measure of how certain we can be that a
specific interval contains the true parameter

what does heterogeneity mean - answer-variation, scatter

what does heterogeneity mean - answer-

most common CI - answer-95%

the bigger the CI the - answer-more uncertainty and less precise inference

the length of CI is - answer-a measure of our level of uncertainty about a parameter
------ *precision of inference*

the smaller CI is - answer-the less uncertainty and more percise our inference

SD measures - answer-scatter in data(dispersion)

what does CI length depend on - answer-sample size (want this to be big) and
random variation(SD)(want this to be small)

Less random variation (smaller sample SD) means - answer-less uncertainty of
inference = better precision.



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