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Q: Differences between two sample averages are most likely to be statistically significant if?
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Continue Learning about Statistics

Can paired means be statistically significant?

No. However, the difference between them can be.


Are the differences between mean and median significant?

yes median is the middle number of the group and mean is the avergage number of the group put together


To decide whether observed differences between samples reflect actual differences between?

statistical significance


What is the difference between a crude odds ration and an adjusted odds ratio?

Odds ratio (AD/BC) is the ratio between number of times that something happens and does not happen. Crude odds ratio is the ratio that is not stratified (ex. by age). Adjusted odds ratio is a stratified odds ratio. If the odds ratio equals one, then there is no association, and null hypothesis shall be accepted. If one is included into confidence interval, then it is possible that odds ratio equals one, and it is not statistically significant. If stratified odds ratios are about the same, or there are no significant differences, the odds ratios are combined into one common odds summary estimate of two stratum specific ORs using Mantel-Haenszel and/or Cohran's tests, or multivariable analysis.


What is the chi square test used for?

The chi-squared test is used to compare the observed results with the expected results. If expected and observed values are equal then chi-squared will be equal to zero. If chi-squared is equal to zero or very small, then the expected and observed values are close. Calculating the chi-squared value allows one to determine if there is a statistical significance between the observed and expected values. The formula for chi-squared is: X^2 = sum((observed - expected)^2 / expected) Using the degrees of freedom, use a table to determine the critical value. If X^2 > critical value, then there is a statistically significant difference between the observed and expected values. If X^2 < critical value, there there is no statistically significant difference between the observed and expected values.