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When are two random samples dependent?
Two random samples are dependent if each data value in one sample can be paired with a corresponding data value in the other sample.
Would the resulting sets of data represent dependent or independent samples?
dependent. because this set of numbers is dependent on what is put into the data table.
What is dependent sample?
Data gathering in two different samples such that there is matching of the first sample data drawn and a corresponding data value in the second sample.
Why do polls have different outcomes?
Because they are based on samples and outcomes vary between different samples.
What do samples in a t test in a data set do?
All that the samples do is enable the observer to make measurements of some characteristic.
When are two samples dependent?
Two random samples are dependent if each data value in one sample can be paired with a corresponding data value in the other sample.
When are two random samples dependent?
Two random samples are dependent if each data value in one sample can be paired with a corresponding data value in the other sample.
Would the resulting sets of data represent dependent or independent samples?
dependent. because this set of numbers is dependent on what is put into the data table.
Can carbon ages can be used as independent or dependent variable?
Either. You could have carbon isotope ratios as your independent and carbon age as your dependent. or You could have the carbon age of soil samples as your independent and the artefacts that you are trying to date as the dependent.
Comparing the means of two normal distribution?
You can compare the means of two dependent or independent samples. You can also set up confidence intervals. For independent samples you test the claim that the two means are not equal; the null hypothesis is mean1 equals mean2. The alternative hypothesis is mean1 does not equal mean2. For dependent (paired) samples you test the claim that the mean of the differences are not equal; the null hypothesis is the difference equals zero; the alternative hypothesis is the difference does not equal zero.
What is dependent sample?
Data gathering in two different samples such that there is matching of the first sample data drawn and a corresponding data value in the second sample.
How is the error term determined?
With fewer degrees of freedom and larger critical values to exceed, how can the dependent samples t be more powerful than the independent t
What is the definition of dependent sample?
two samples are independent if they are drawn from two different populations, and/ or the samples have no effect on each other. eg: We want to estimate the difference between the mean salaries of all male and all female executives. We draw one sample from the population of male executives and another from the population of female executives. These two samples are independent because they come from different populations and the samples have no effect on each other Rate This Answer
Do i say can i have samples about them or samples of them?
samples of them
How to take samples to Mexico?
Samples of what?
What is the birth name of Junior Samples?
Junior Samples's birth name is Samples, Alvin.
When a researcher has two samples with two means one of the assumptions for two samples is independence of between the two samples What does this mean What happens if the independence assumption is?
Independence of the two samples means that the choosing of the first sample did not influence the choosing of the other sample, and vice versa. For example, if you were comparing running speed in two different brands of running shoes, you could look at two samples of people running a 100 m dash -- one sample of people running in Brand A and one sample of people running in Brand B. If those two groups were picked independently of one another, these samples would be independent. If, instead, you had the same group of people run the race twice (once in each brand of shoe), these samples would be dependent. Samples that are not independent are said to be "correlated", "interdependent", or "dependent". Because the two samples are correlated, you might get incorrect findings for your statistical study. For example, say you want to compare the heights of boys and girls. If you chose the samples by choosing a girl for the girl sample, then choosing her brother for the boy sample, your statistical analyses might be misleading if you didn't account for the fact that tall girls are more likely to have tall brothers, and short girls are more likely to have short brothers. By choosing siblings for the two groups, you have made the two samples not independent of one another. If the independence assumption is violated, you have to do a special type of statistical test. For example, instead of doing a two-sample t-test, you would have to do a paired t-test.
