What are the conditions for the validity of t-test?

What are the conditions for the validity of t-test?

The conditions required to conduct a t-test include the measured values in ratio scale or interval scale, simple random extraction, homogeneity of variance, appropriate sample size, and normal distribution of data.

What conditions must be met for T distribution?

The population distribution is symmetric, unimodal, without outliers, and the sample size is at least 30. The population distribution is moderately skewed, unimodal, without outliers, and the sample size is at least 40.

What are the conditions for a 2 sample t-test?

Two-sample t-test assumptions

• Data values must be independent.
• Data in each group must be obtained via a random sample from the population.
• Data in each group are normally distributed.
• Data values are continuous.
• The variances for the two independent groups are equal.

Can you use t-test with outliers?

For the t-test on independent samples, the data in each sample must be normal or at least reasonably symmetric and that the presence of outliers does not distort either of these results.

What are the 3 assumptions for an independent measures t-test?

Normality. the data for each group should be approximately normally distributed. Homogeneity of variances. the variance of the outcome variable should be equal in each group.

What are the three characteristics of t-distribution?

Three characteristics of distributions. There are 3 characteristics used that completely describe a distribution: shape, central tendency, and variability.

Under what circumstances should a T interval be constructed?

When to use a t-interval. The rules for when to use a t-interval are as follows. Use a t-interval when: Population standard deviation UNKNOWN and original population normal OR sample size greater than or equal to 30 and Population standard deviation UNKNOWN.

Which of the following conditions must be met in order to conduct an independent samples t-test?

1.) Parent populations from which samples are drawn are normally distributed. 2.) The two samples are random and independent of each other.

What is the 10% condition?

The 10% condition states that sample sizes should be no more than 10% of the population. Whenever samples are involved in statistics, check the condition to ensure you have sound results. Some statisticians argue that a 5% condition is better than 10% if you want to use a standard normal model.

Do t-tests work on skewed data?

Unless the skewness is severe, or the sample size very small, the t test may perform adequately. Whether or not the population is skewed can be assessed either informally (including graphically), or by examining the sample skewness statistic or conducting a test for skewness.

Does t-test require normality?

t-test DOES require normality of the population. That’s an assumption needed for the t statistic to have a t-Student distribution. If you don’t have a normal population, you can’t express the t statistic as a standard normal variable divided by the root of a Chi-squared variable divided by its degrees of freedom.

How do you analyze data that is not normally distributed?

There are two ways to go about analyzing the non-normal data. Either use the non-parametric tests, which do not assume normality or transform the data using an appropriate function, forcing it to fit normal distribution. Several tests are robust to the assumption of normality such as t-test, ANOVA, Regression and DOE.

Can you do t-test on skewed data?

How many groups of participants are appropriate when using an independent t-test?

two separate groups
The independent t-test is used when you have two separate groups of individuals or cases in a between-participants design (for example: male vs female; experimental vs control group).

What are different types of t tests?

There are three types of t-tests we can perform based on the data at hand: One sample t-test. Independent two-sample t-test….Paired Sample t-test

• t = t-statistic.
• m = mean of the group.
• µ = theoretical value or population mean.
• s = standard deviation of the group.
• n = group size or sample size.