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Chemistry Work
1. Water Vaporization apply. Make sure that you are showing each step of your work. 1. How much energy is absorbed when 30 ...
Chemistry Work
1. Water Vaporization apply. Make sure that you are showing each step of your work. 1. How much energy is absorbed when 30.3 g of liquid water boils?
You are a manager working for an insurance, discussion help
You are a manager working for an insurance company. Your job entails processing individual claims filed by policyholders. ...
You are a manager working for an insurance, discussion help
You are a manager working for an insurance company. Your job entails processing individual claims filed by policyholders. In general, most claims are relatively minor, costwise, but a few are quite expensive. Each quarter, you compile a report summarizing key claims statistics that includes the number of claims submitted, the mean cost per claim, the median cost per claim, the proportion of claims being litigated, the number of emergency procedures, the proportion of men versus women, and the average age of claimants. Your measures are computed separately for the southern and northern regions, and you are interested in determining whether or not there are statistically significant differences between the two regions on each of the aforementioned measures.Evaluate which comparisons would require the use of the t-test and which would use the chi-squared test.Explain your answers. Support your discussion with relevant examples, research, and rationale. 500 words
UMGC Correlation Misinterpreted as Caution Discussion
Topic 1:One goal of statistics is to identify relations among variables. What happens to one variable as another variable ...
UMGC Correlation Misinterpreted as Caution Discussion
Topic 1:One goal of statistics is to identify relations among variables. What happens to one variable as another variable change? Does a change in one variable cause a change in another variable? These questions can lead to powerful methods of predicting future values through linear regression.It is important to note the true meaning and scope of correlation, which is the nature of the relation between two variables. Correlation does not allow to say that there is any causal link between the two variables. In other words, we cannot say that one variable causes another; however, it is not uncommon to see such use in the news media. An example is shown below.Here we see that, at least visually, there appears to be a relation between the divorce rate in Maine and the per capita consumption of margarine. Does this imply that all married couples in Maine should immediately stop using margarine in order to stave off divorce? Common sense tells us that is probably not true.This is an example of a spurious correlation in which there appears to be a relation between the divorce rate and margarine consumption but, it is not a causal link. The appearance of such a relation could merely be due to coincidence or perhaps another unseen factor.What is one instance where you have seen correlation misinterpreted as causation? Please describe in a clear fashion.
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Most Popular Content
4 pages
Chemistry Work
1. Water Vaporization apply. Make sure that you are showing each step of your work. 1. How much energy is absorbed when 30 ...
Chemistry Work
1. Water Vaporization apply. Make sure that you are showing each step of your work. 1. How much energy is absorbed when 30.3 g of liquid water boils?
You are a manager working for an insurance, discussion help
You are a manager working for an insurance company. Your job entails processing individual claims filed by policyholders. ...
You are a manager working for an insurance, discussion help
You are a manager working for an insurance company. Your job entails processing individual claims filed by policyholders. In general, most claims are relatively minor, costwise, but a few are quite expensive. Each quarter, you compile a report summarizing key claims statistics that includes the number of claims submitted, the mean cost per claim, the median cost per claim, the proportion of claims being litigated, the number of emergency procedures, the proportion of men versus women, and the average age of claimants. Your measures are computed separately for the southern and northern regions, and you are interested in determining whether or not there are statistically significant differences between the two regions on each of the aforementioned measures.Evaluate which comparisons would require the use of the t-test and which would use the chi-squared test.Explain your answers. Support your discussion with relevant examples, research, and rationale. 500 words
UMGC Correlation Misinterpreted as Caution Discussion
Topic 1:One goal of statistics is to identify relations among variables. What happens to one variable as another variable ...
UMGC Correlation Misinterpreted as Caution Discussion
Topic 1:One goal of statistics is to identify relations among variables. What happens to one variable as another variable change? Does a change in one variable cause a change in another variable? These questions can lead to powerful methods of predicting future values through linear regression.It is important to note the true meaning and scope of correlation, which is the nature of the relation between two variables. Correlation does not allow to say that there is any causal link between the two variables. In other words, we cannot say that one variable causes another; however, it is not uncommon to see such use in the news media. An example is shown below.Here we see that, at least visually, there appears to be a relation between the divorce rate in Maine and the per capita consumption of margarine. Does this imply that all married couples in Maine should immediately stop using margarine in order to stave off divorce? Common sense tells us that is probably not true.This is an example of a spurious correlation in which there appears to be a relation between the divorce rate and margarine consumption but, it is not a causal link. The appearance of such a relation could merely be due to coincidence or perhaps another unseen factor.What is one instance where you have seen correlation misinterpreted as causation? Please describe in a clear fashion.
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