Question

explain the difference between effect size and confidence interval.

Answer #1

Effect size

- Effect size is a statistical concept that measures the strength of the relationship between two variables on a numeric scale.
- Statistic effect size helps us in determining if the difference is real or if it is due to a change of factors.
- the effect size is usually measured in three ways: (1) standardized mean difference, (2) odd ratio, (3) correlation coefficient.

Confidence interval

- confidence interval, in statistics, refers to the probability that a population parameter will fall between two set values for a certain proportion of times. Confidence intervals measure the degree of uncertainty or certainty in a sampling method.
- A confidence interval can take any number of probabilities, with the most common being a 95% or 99% confidence level.
- Statisticians use confidence intervals to measure uncertainty.

A. which confidence interval is wider? The 95%
confidence interval or the 99% confidence interval?
difference for both confidence intervals: 0.109
95% CI for difference: (-0.123, 0.340)
99% CI for difference: (-0.199, 0.416)
B. Given an arbitrary data set, is there a general
relationship between confidence level and the width of the
confidence interval? Explain.
Please make the answers to parts A and B detailed and easy to
read and follow, thank you :)

What is the difference between statistical testing and effect
size?

When a confidence interval for the difference between two means
obtained in an experiment includes the hypothesized value, the
researcher can conclude that...
the results for the effect of the independent variable are
inconclusive
the independent variable had an effect
the independent variable did not have an effect.
the results for the effect of the independent variable will
likely be replicated

Find a 95% confidence interval for the difference between the
two population means.

What is the difference between a Point Estimate and a Confidence
Interval? Provide an example for both

At 90% confidence interval, is there a difference between the
means of Branch 1 and Branch 4?
Given that MSE= 26006.25
Branch1
Branch2
Branch3
Branch4
500
500
440
450
550
700
810
750
570
340
700
500
800
710
650
800
sample size
n1=4
n2=4
n3=4
n4=4
ntotal=16
sample mean
x1=605
x2=652.5
x3=650
x4=625
x3=610.625
sample standard deviation
s1=133.291
s2=177.082
s3=155.134
s4=175.594
sG=147.985
1 - The confidence interval is:
2 - The best explanation of the confidence interval result
is:...

Which of the following is correct for confidence interval?
As the sample size decreases, confidence interval gets
narrower.
As the confidence level increases, confidence interval gets
broader.
As the sample size increases, confidence interval gets
broader.
As the confidence level increases, confidence interval gets
narrower.

Paired T confidence interval:
μD = μ1 - μ2 : Mean of the
difference between Male Population and Female Population
90% confidence interval results:
Difference
Mean
Std. Err.
DF
L. Limit
U. Limit
Male Population - Female Population
-4443.9378
721.71083
594
-5632.9008
-3254.9748
Why is the above data paired? Interpret and state your
confidence Interval, and based on your confidence interval is there
a significant difference in male and female populations; if so what
is it and how do you...

construct a 95% confidence interval estimate of the population
slope between assesed value and size.

Construct the indicated confidence interval for the difference
between population proportions p1-p2 . Assume
that the samples are independent and that they have been randomly
selected.
x1 = 11, n1 = 45 and x2 = 18,
n2 = 54; Construct a 90% confidence interval for the
difference between population proportions p1 -
p2.
0.094 <p1 - p2 < 0.395
0.067 <p1 - p2 < 0.422
-0.238 <p1 - p2 < 0.060
0.422 <p1 - p2 < 0.065

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