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A chi-square statistic can be large if either there is a large difference between the observed and expected values for one or more categories. However, it can also be large if the expected value in a category is very small.
In the first case, it is likely that the data are not distributed according to the null hypothesis. In the second case, it can often mean that that, because of low expected values, adjacent categories need to be combined before the chi-square statistic is calculated.
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Which combination of factors is most likely to produce a significant value for an independent-measures t statistic?
To know which combination of factors is most likely to produce a significant value it is important to know what the factors are. Without knowing what factors there are to choose from it is hard to know what the answer is.
Will a large sample size and a small sample variance produce the largest value for the estimated standard error?
no
What is a t value?
It is a value of a test statistic based on the Student's t distribution.
What does the test statistic measure?
The test statistic is a measure of how close the sample proportion is to the null value.
What sample statistic is used to estimate a population parameter?
A point estimate is a single value (statistic) used to estimate a population value (parameter)true apex
What do large values of a chi square statistic indicate?
A large value for the chi-squared statistic indicates that one should be suspiciuous of the null hypothesis, because the expected values and the observed values willdiffer by a large amount
What combination of factors is most likely to produce a large value for the F-ratio?
a large mean differecnce and large sample variance
What combination of factors is most likely to produce a large value for the F ratio?
a large mean differecnce and large sample variance
Which combination of factors is most likely to produce a significant value for an independent-measures t statistic?
To know which combination of factors is most likely to produce a significant value it is important to know what the factors are. Without knowing what factors there are to choose from it is hard to know what the answer is.
What combination of factors will produce the smallest value for the standard error?
A small sample and a large standard deviation
Will a large sample size and a small sample variance produce the largest value for the estimated standard error?
no
If you select a large enough sample size can you reject any null hypothesis?
The simple answer is no. This depends on a lot of factors such as alpha which determines the critical value and the absolute value of the difference between the claim and sample data. Mathematically speaking, all things being equal, the larger the sample size the larger the absolute value of the test statistic. The formula for the test statistic mean with sigma known is shown below. You can substitute values in and perform the mathematics. The larger the sample size, the larger the Z value; but note if the numerator is small, even a small denominator will not produce a large Z value. In fact, the numerator could be zero which would make the test statistic zero. Z = (Xbar - μxbar)/(σ/√n) (formula from Elementary Statistics by Mario F. Triola)
Large ions tend to produce a more negative value for lattice energy than smaller ions do?
True,
How do you find p value with test statistic and critical value?
Normally you would find the critical value when given the p value and the test statistic.
Which of the following samples will produce the largest value for the estimated standard error?
A small sample size and a large sample variance.
What is a t value?
It is a value of a test statistic based on the Student's t distribution.
What does the test statistic measure?
The test statistic is a measure of how close the sample proportion is to the null value.
