a. Systematic reviews and meta-analyses are the same.

b. Census studies determine casual relationships.

c. Qualitative and quantitative data collection methods produce the same level of evidence.

d. none of the above

musicbachv7
2022-08-12
Answered

Which of the following statements is true?

a. Systematic reviews and meta-analyses are the same.

b. Census studies determine casual relationships.

c. Qualitative and quantitative data collection methods produce the same level of evidence.

d. none of the above

a. Systematic reviews and meta-analyses are the same.

b. Census studies determine casual relationships.

c. Qualitative and quantitative data collection methods produce the same level of evidence.

d. none of the above

You can still ask an expert for help

Cynthia Lester

Answered 2022-08-13
Author has **22** answers

$\cdot $ First is True because A systematic review attempts to gather all available empirical research by using clearly defined, systematic methods to obtain answers to a specific question. A meta-analysis is the statistical process of analyzing and combining results from several similar studies. So both are same;

$\cdot $ Second is wrong because sample studies determines casual relationship;

$\cdot $ Third is wrong because Qualitative data and quantitative data collection methods produce the different level of evidence. Even we can say that Quantitative data is more useful and have good estimates.)

Answer : True statements is

Systematic reviews and meta-analyses are the same.

$\cdot $ Second is wrong because sample studies determines casual relationship;

$\cdot $ Third is wrong because Qualitative data and quantitative data collection methods produce the different level of evidence. Even we can say that Quantitative data is more useful and have good estimates.)

Answer : True statements is

Systematic reviews and meta-analyses are the same.

asked 2022-07-11

Assume the random variable X has a binomial distribution with the given probability of obtaining a success. Find the following probability, given the number of trials and the probability of obtaining a success. Round your answer to four decimal places.

P(X>2)$P\left(X>2\right)$, n=6$n=6$, p=0.7

asked 2022-07-16

I came here since I know this is the best place to ask a question.

I'm a first year student who changed his major to applied mathematics. In middle school I was a garbage math student, but I realized the importance of math in high school when I was introduced to amazing teachers who truly loved what they did. I put myself in tougher classes and eventually got to AP calculus. There was an error in my idea, I never really got a deep understanding of the stuff I was doing and was struggling since I didn't understand the basics and never really did practice problems.

This year I began to start over from scratch from pre-algebra working to pre-calculus. Even though I have already took Calculus.

I'm in a introduction to research class this semester and we are preforming a meta-analysis of some random topic and then presenting at the end of the semester. I'm really enjoying it, and I will definitely apply for more research as I progress through my undergraduate career. (Urge to Compute)

I know I'll probably never win a field's medal, but I'm really intimidated and humbled by the near perfect SAT math scores and Math Olympiad participants.

It's too late for me to have that, but the best quality I have is sticking with the concepts and problems until I can explain them to my dog. (Basically until I understand it)

I'm really sorry for the long post / soft question, I've just been thinking about this since 11th grade but never asked anyone about it.

Basically I'm just wondering if I'm wasting my time, and if there have been mathematicians that were in a similar situation. (Famous or not.)

Again, sorry for the soft question and thank you for taking the time to read this!

I'm a first year student who changed his major to applied mathematics. In middle school I was a garbage math student, but I realized the importance of math in high school when I was introduced to amazing teachers who truly loved what they did. I put myself in tougher classes and eventually got to AP calculus. There was an error in my idea, I never really got a deep understanding of the stuff I was doing and was struggling since I didn't understand the basics and never really did practice problems.

This year I began to start over from scratch from pre-algebra working to pre-calculus. Even though I have already took Calculus.

I'm in a introduction to research class this semester and we are preforming a meta-analysis of some random topic and then presenting at the end of the semester. I'm really enjoying it, and I will definitely apply for more research as I progress through my undergraduate career. (Urge to Compute)

I know I'll probably never win a field's medal, but I'm really intimidated and humbled by the near perfect SAT math scores and Math Olympiad participants.

It's too late for me to have that, but the best quality I have is sticking with the concepts and problems until I can explain them to my dog. (Basically until I understand it)

I'm really sorry for the long post / soft question, I've just been thinking about this since 11th grade but never asked anyone about it.

Basically I'm just wondering if I'm wasting my time, and if there have been mathematicians that were in a similar situation. (Famous or not.)

Again, sorry for the soft question and thank you for taking the time to read this!

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When is meta-analysis is most useful?

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My main goal is to calculate the sampling variance. But I will start with the standard deviation. I am doing a meta-analysis and need to calculate the variance for EACH effect size (prevalence in this case) in each study.

For example, I have 10 positive cases out of 1000 people that were tested. This gives a prevalence of 0.01 (or 1%). How do I find the standard deviation from this information?

For example, I have 10 positive cases out of 1000 people that were tested. This gives a prevalence of 0.01 (or 1%). How do I find the standard deviation from this information?

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What measure of effect size would most likely be used in each of the following meta-analyses?

a. A meta-analysis on the effect of the drug ibuprofen on the frequency of individuals contracting kidney disease.

b. A meta-analysis of whether excluding parasites from a population affects mean growth rate.

c. A meta-analysis of the association between human height and life span

d. A meta-analysis comparing the survival of parasitized and unparasitized birds.

e. A meta-analysis comparing the difference in body size of males and females across species.

a. A meta-analysis on the effect of the drug ibuprofen on the frequency of individuals contracting kidney disease.

b. A meta-analysis of whether excluding parasites from a population affects mean growth rate.

c. A meta-analysis of the association between human height and life span

d. A meta-analysis comparing the survival of parasitized and unparasitized birds.

e. A meta-analysis comparing the difference in body size of males and females across species.

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Explain what Cohen's d and ${r}^{2}$ measure when calculated for a t test

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Use this type of statistics to analyze data when you have more than one dependent variable.

Use one of the following key terms to answer each of the following questions.

KEY TERM BANK (separated by commas):

Univariate, Multivariate, meta-analysis, F-ratio, interaction, main effect

Use one of the following key terms to answer each of the following questions.

KEY TERM BANK (separated by commas):

Univariate, Multivariate, meta-analysis, F-ratio, interaction, main effect