Recent questions in Effect Size

Descriptive StatisticsAnswered question

Nola Nunez 2023-02-18

What is the effect of wind speed on evaporation?

Descriptive StatisticsAnswered question

Davirnoilc 2022-11-20

What is the relationship between effect size and sample size ?

- when the effect size is small large sample are needed

- when the effect size is large,large samples are needed

- regardless of effect size,large sample are generally necessary

- effect size and sample size are dependent on level power

- when the effect size is small large sample are needed

- when the effect size is large,large samples are needed

- regardless of effect size,large sample are generally necessary

- effect size and sample size are dependent on level power

Descriptive StatisticsAnswered question

Ty Moore 2022-11-16

As the effect size increases the power of a hypothesis test also increases, but what happens to alpha?

Descriptive StatisticsAnswered question

sbrigynt7b 2022-11-14

Given a non-empty integer array of size n, find the minimum number of moves it takes to make all the integers equal, where a move means incrementing n-1 integers by 1.

It turns out that incrementing n-1 numbers has the "same effect" as decrementing a single number. By "same effect", I mean it takes the same number of steps to make all the integers equal. Basically, I find the minimum element and return the sum of differences for all the integers in the array.

However, I could not prove that this was the case. I got the correct answer but it was more of a guess. How can a proof be constructed to show that the two strategies would take the same number of steps?

It turns out that incrementing n-1 numbers has the "same effect" as decrementing a single number. By "same effect", I mean it takes the same number of steps to make all the integers equal. Basically, I find the minimum element and return the sum of differences for all the integers in the array.

However, I could not prove that this was the case. I got the correct answer but it was more of a guess. How can a proof be constructed to show that the two strategies would take the same number of steps?

Descriptive StatisticsAnswered question

kunguwaat81 2022-11-10

Which of the following is true when thinking about statistical significance and effect sizes?

A. A statistically significant effect will always have a meaningful effect size.

B. A large effect size is will always be statistically significant.

C. A statistically non-significant effect can have a large effect size.

A. A statistically significant effect will always have a meaningful effect size.

B. A large effect size is will always be statistically significant.

C. A statistically non-significant effect can have a large effect size.

Descriptive StatisticsAnswered question

spasiocuo43 2022-11-04

Which of the following statements about effect size is true?

$\u25fb$ A larger difference between the population means leads to a smaller effect size.

$\u25fb$ Sample size (n) does not change the effect size.

$\u25fb$ A larger sample leads to a smaller effect size.

$\u25fb$ The difference between the populations means does not change the effect size.

$\u25fb$ A larger difference between the population means leads to a smaller effect size.

$\u25fb$ Sample size (n) does not change the effect size.

$\u25fb$ A larger sample leads to a smaller effect size.

$\u25fb$ The difference between the populations means does not change the effect size.

Descriptive StatisticsAnswered question

shiya43 2022-10-22

When looking at effect size, Cohen's dis 2.03. What does this indicate for effect size?

It does not pass the effect size test

The effect size is small

The effect size is medium

The effect size is large

It does not pass the effect size test

The effect size is small

The effect size is medium

The effect size is large

Descriptive StatisticsAnswered question

snaketao0g 2022-10-22

For a z-test for one proportion, a possible effect size measure is

$(p\u2013{p}_{0})/\sqrt{{p}_{0}(1-{p}_{0})}$

where ${P}_{0}$ is the null value and p is the true population proportion, which can be estimated using the sample proportion. What is the relationship between this effect size and the z-test statistic for this situation? Does the effect size fit the relationship "Test statistic = Size of effect x Size of study"? If not, explain why not. If so, show how it fits. What would be a reasonable way to estimate this effect size?

$(p\u2013{p}_{0})/\sqrt{{p}_{0}(1-{p}_{0})}$

where ${P}_{0}$ is the null value and p is the true population proportion, which can be estimated using the sample proportion. What is the relationship between this effect size and the z-test statistic for this situation? Does the effect size fit the relationship "Test statistic = Size of effect x Size of study"? If not, explain why not. If so, show how it fits. What would be a reasonable way to estimate this effect size?

Descriptive StatisticsAnswered question

Kathy Guerra 2022-10-09

Showing power curves for a one-sided t-test. Use the figure to give the approximate power in each of the following situations, and write a sentence explaining what probability is represented by the power. n = 20, true effect size = 0.4. n = 50, true effect size = 0.4. n = 100, true effect size = 0.4. n = 20, true effect size = 0.7.

Descriptive StatisticsAnswered question

Krish Crosby 2022-09-25

Based on the effect size conventions, $d=0.60$ is a

(a)small effect size

(b)medium effect size

(c)large effect size

(a)small effect size

(b)medium effect size

(c)large effect size

Descriptive StatisticsAnswered question

Ratuiszt 2022-09-06

What would be true regarding the effect size for the following?

t ratio 3.201

Sample size (n) -20

- A medium effect size is present.

- A small effect size is present.

- The effect size is neither small nor medium.

- A strong effect size is present.

t ratio 3.201

Sample size (n) -20

- A medium effect size is present.

- A small effect size is present.

- The effect size is neither small nor medium.

- A strong effect size is present.

Descriptive StatisticsAnswered question

corniness9a 2022-09-06

Based on the effect size table covered in class, d 0.18 is a

A. medium effect size

B. insignificant result

C. small effect size

D. large effect size

A. medium effect size

B. insignificant result

C. small effect size

D. large effect size

Descriptive StatisticsAnswered question

Isaac Barry 2022-09-04

Working on a problem related to effect size, I get this relation where

$Q=\mathrm{log}(m)(m-\frac{1}{m})$

The domain of $m$ is $]0,\mathrm{\infty}[$. For a given $Q$, whenever I find a $m={m}^{\ast}$ satisfying the equality, the equality is also satisfied with $m=1/{m}^{\ast}$. Therefore, I can limit the domain of $m$ to $]1,\mathrm{\infty}[$.

Is there a formula that can isolate $m$ so that given a value $Q$ ($Q\in {\mathbb{R}}^{+}$), $m$ follows?

$Q=\mathrm{log}(m)(m-\frac{1}{m})$

The domain of $m$ is $]0,\mathrm{\infty}[$. For a given $Q$, whenever I find a $m={m}^{\ast}$ satisfying the equality, the equality is also satisfied with $m=1/{m}^{\ast}$. Therefore, I can limit the domain of $m$ to $]1,\mathrm{\infty}[$.

Is there a formula that can isolate $m$ so that given a value $Q$ ($Q\in {\mathbb{R}}^{+}$), $m$ follows?

Descriptive StatisticsAnswered question

fofopausiomiava 2022-09-03

Which of the following is true regarding effect size?

0.10 - 0.29 = small

0.30 - 0.49 = moderate

0.50 - 1 - large

All of the above are true

0.10 - 0.29 = small

0.30 - 0.49 = moderate

0.50 - 1 - large

All of the above are true

Descriptive StatisticsOpen question

Macy Villanueva 2022-08-30

Characteristics of effect size includes all of the following, EXCEPT FOR:

- A study's outcome is always clinically significant (large effect size) if it is statistically significant

- A small effect size would not show an obvious difference between groups as compared to a large effect size Effect size evaluates the magnitude of a relative difference or a magnitude of a ratio of variances

- Effect size is used in assessing clinical significance

- A practitioner would be more likely to recommend a therapy with a large effect size than a small effect size

- A study's outcome is always clinically significant (large effect size) if it is statistically significant

- A small effect size would not show an obvious difference between groups as compared to a large effect size Effect size evaluates the magnitude of a relative difference or a magnitude of a ratio of variances

- Effect size is used in assessing clinical significance

- A practitioner would be more likely to recommend a therapy with a large effect size than a small effect size

Descriptive StatisticsOpen question

Expositur3e 2022-08-22

We discussed five different measures of effect size for chi-square tests: Three of which belong to the d-family effect size; Two of which belong to the r- family effect size. List the name of all five measures of effect size.

Descriptive StatisticsOpen question

Jaydin Harvey 2022-08-20

Name two different ways to measure effect size.

Effect size measures the size of the effect of what on what?

How do the two measures of effect size differ?

Why do we measure effect size?

When do we measure effect size?

Effect size measures the size of the effect of what on what?

How do the two measures of effect size differ?

Why do we measure effect size?

When do we measure effect size?

Descriptive StatisticsOpen question

trokusr 2022-08-19

In a planned study, there is a known population with a normaldistribution, $\mu =20$,and $\sigma =4$.

What is the predicted mean if the researcher predicts

(a) a small positive effect size,

(b) a medium negative effect size,

(c) a large positive effect size,

(d) an effect size of $d=0.55$,

(e) an effect size of $\sigma =4$?

What is the predicted mean if the researcher predicts

(a) a small positive effect size,

(b) a medium negative effect size,

(c) a large positive effect size,

(d) an effect size of $d=0.55$,

(e) an effect size of $\sigma =4$?

Descriptive StatisticsAnswered question

empalhaviyt 2022-08-14

HST is perhaps most focused on two primary values - the p-value and the effect size.

In your own words, what is a p-value? What does it mean when an analysis produces a p-value of .03?

In your own words, what is an effect size? Provide an example of a small effect size and one of a large effect size and explain why the effect size would matter in each case.

In your own words, what is a p-value? What does it mean when an analysis produces a p-value of .03?

In your own words, what is an effect size? Provide an example of a small effect size and one of a large effect size and explain why the effect size would matter in each case.

Descriptive StatisticsAnswered question

Ronnie Rojas 2022-08-10

Describe how the following are related:

a. Statistical significance and effect size

b. Difference between means and effect size

c. Effect size and variability

d. Sample size and power of a statistical test

e. Effect size and power of a statistical test

a. Statistical significance and effect size

b. Difference between means and effect size

c. Effect size and variability

d. Sample size and power of a statistical test

e. Effect size and power of a statistical test

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Effect-size is a statistical measure used to determine the size of the observed effect of an intervention or experiment on an outcome. It helps to compare the magnitude of an effect between different experiments or studies and to determine the statistical significance of the results. Effect-size is determined using questions, equations and answers to calculate the size of an effect relative to the variability of the sample. Researchers and students seeking assistance with effect-size calculations can find help in online forums, textbooks and tutorials. Effect-size can be used to help make decisions about whether an intervention has had a meaningful effect or not.