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When are two random samples independent?
z test
What conditions are necessary in order to use a test to test the differences between two population means?
The samples must be randomly selected, independent, and normally distributed. The following are necessary to use a t-test for small independent samples. 1. The samples must be randomly selected. 2. The samples must be independent. 3. Each population must have a normal distribution.
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.
What is Independent Sampling?
Data gathered i n two different samples such as the sample data drawn from one population is completely unrelated to the section of sample data,
Which conditions must be met to conduct a test for the difference in two sample means?
The two samples must be independent and the data must be at least ordinal. Under those conditions the Mann-Whitney U test can be used.
When are two random samples independent?
z test
What conditions are necessary in order to use a test to test the differences between two population means?
The samples must be randomly selected, independent, and normally distributed. The following are necessary to use a t-test for small independent samples. 1. The samples must be randomly selected. 2. The samples must be independent. 3. Each population must have a normal distribution.
What conditions are necessary in order to use a t-test to test the differences between two population means?
The samples must be randomly selected, independent, and normally distributed. The following are necessary to use a t-test for small independent samples. 1. The samples must be randomly selected. 2. The samples must be independent. 3. Each population must have a normal distribution.
When independent sample t test is used?
The Independent Samples T Test compares the mean scores of two groups on a given variable.
Definition of independent 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
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
What is a comparison microscope?
A comparison microscope is a specialized microscope that has two separate optical systems, allowing for side-by-side comparison of two samples simultaneously. This type of microscope is commonly used in forensics for comparing specimens such as hairs, fibers, or bullets. It helps in identifying similarities or differences between the samples being examined.
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.
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.
How can DNA be used to determine the kinship of two organisms?
Upon comparison of genetic samples the alleles in the DNA can determine kinship of two organisms. Kinship can be determined paternally or maternally in the case of mitrochondrial DNA analysis.
What is Independent Sampling?
Data gathered i n two different samples such as the sample data drawn from one population is completely unrelated to the section of sample data,
What are the two phases in a forensic scientist's analytical scheme?
The two phases in a forensic scientist's analytical scheme are identification and comparison. Identification involves determining the nature or category of evidence collected, while comparison involves comparing the evidence with known samples to establish possible links or associations.
