Should I use chi-square or t test? The easiest way to know whether or not to use a chi-square test vs. a t-test is to simply look at the types of variables you are working with. If you have two variables that are both categorical, i.e. they can be placed in categories like male, female and republican, democrat, independent, then you should use a chi-square test.
When should chi-square not be used?
Most recommend that chi-square not be used if the sample size is less than 50, or in this example, 50 F2 tomato plants. If you have a 2x2 table with fewer than 50 cases many recommend using Fisher's exact test.
Are t-test and ANOVA the same?
The t-test is a method that determines whether two populations are statistically different from each other, whereas ANOVA determines whether three or more populations are statistically different from each other.
What are the limitations of t test?
Test limitations include sensitivity to sample sizes, being less robust to violations of the equal variance and normality assumptions when sample sizes are unequal  and performing better with large sample sizes  . T-tests were used in our study to compare means between groups for continuous variables.
What are the weaknesses of a chi-square test?
Limitations include its sample size requirements, difficulty of interpretation when there are large numbers of categories (20 or more) in the independent or dependent variables, and tendency of the Cramer's V to produce relative low correlation measures, even for highly significant results.
Related question for Should I Use Chi-square Or T Test?
What does chi-square test tell you?
The chi-square test is a hypothesis test designed to test for a statistically significant relationship between nominal and ordinal variables organized in a bivariate table. In other words, it tells us whether two variables are independent of one another.
How do you know what t-test to use?
If you are studying one group, use a paired t-test to compare the group mean over time or after an intervention, or use a one-sample t-test to compare the group mean to a standard value. If you are studying two groups, use a two-sample t-test. If you want to know only whether a difference exists, use a two-tailed test.
How do you carry out a t-test?
What is the difference between a paired and unpaired t-test?
A paired t-test is designed to compare the means of the same group or item under two separate scenarios. An unpaired t-test compares the means of two independent or unrelated groups. In an unpaired t-test, the variance between groups is assumed to be equal.
Which is better ANOVA or t-test?
There is a thin line of demarcation amidst t-test and ANOVA, i.e. when the population means of only two groups is to be compared, the t-test is used, but when means of more than two groups are to be compared, ANOVA is preferred.
Why do we run an ANOVA instead of multiple t tests?
Why not compare groups with multiple t-tests? Every time you conduct a t-test there is a chance that you will make a Type I error. An ANOVA controls for these errors so that the Type I error remains at 5% and you can be more confident that any statistically significant result you find is not just running lots of tests.
What is the benefit of a t-test?
Essentially, a t-test allows us to compare the average values of the two data sets and determine if they came from the same population.
Are t tests reliable?
The T-test appears to be highly reliable and measures a combination of components, including leg speed, leg power, and agility, and may be used to differentiate between those of low and high levels of sports participation.
Why is chi-square test good?
The chi-square test helps us answer the above question by comparing the observed frequencies to the frequencies that we might expect to obtain purely by chance. Chi-square test in hypothesis testing is used to test the hypothesis about the distribution of observations/frequencies in different categories.
What does it mean if chi-square is not significant?
Among statisticians a chi square of . 05 is a conventionally accepted threshold of statistical significance; values of less than . NS indicates that the chi-square is not significant using the . 05 threshold.
When should you use an independent samples t test?
The Independent Samples t Test is commonly used to test the following: Statistical differences between the means of two groups. Statistical differences between the means of two interventions. Statistical differences between the means of two change scores.
How does a chi-square test work?
The chi-square test of independence works by comparing the categorically coded data that you have collected (known as the observed frequencies) with the frequencies that you would expect to get in each cell of a table by chance alone (known as the expected frequencies).
What do you do after chi-square test?
Following a Chi-Square test that includes an explanatory variable with 3 or more groups, we need to subset to each possible paired comparison. When interpreting these paired comparisons, rather than setting the α-level (p-value) at 0.05, we divide 0.05 by the number of paired comparisons that we will be making.
Is t-test a research design?
The t-test assesses whether the means of two groups are statistically different from each other. This analysis is appropriate whenever you want to compare the means of two groups, and especially appropriate as the analysis for the posttest-only two-group randomized experimental design.
How do you do a t-test in data analysis?
What are the assumptions of t-test?
The common assumptions made when doing a t-test include those regarding the scale of measurement, random sampling, normality of data distribution, adequacy of sample size, and equality of variance in standard deviation.
When should you use the t-test?
T-test. A t-test is used to compare the mean of two given samples. Like a z-test, a t-test also assumes a normal distribution of the sample. A t-test is used when the population parameters (mean and standard deviation) are not known.
How do you write t-test results?
The basic format for reporting the result of a t-test is the same in each case (the color red means you substitute in the appropriate value from your study): t(degress of freedom) = the t statistic, p = p value. It's the context you provide when reporting the result that tells the reader which type of t-test was used.
What is the main difference between a regular t-test and a paired t-test?
Two-sample t-test is used when the data of two samples are statistically independent, while the paired t-test is used when data is in the form of matched pairs.
What is the difference between independent and dependent t-test?
What is the difference between a test of independent means and a test of dependent means? A t-test for independent means test two distinct groups of participants, each group is tested once. -A test for dependent means tests one group of participants, and each participant is tested twice.
Is a Student's t-test paired or unpaired?
Paired t-test compares study subjects at 2 different times (paired observations of the same subject). Unpaired t-test (aka Student's test) compares two different subjects.
What is unique about chi-square analysis?
The Chi-Square Test of Independence determines whether there is an association between categorical variables (i.e., whether the variables are independent or related). It is a nonparametric test. This test is also known as: Chi-Square Test of Association.
Can I use ANOVA for two groups?
Typically, a one-way ANOVA is used when you have three or more categorical, independent groups, but it can be used for just two groups (but an independent-samples t-test is more commonly used for two groups).
What are the different types of chi-square tests?
There are three types of Chi-square tests, tests of goodness of fit, independence and homogeneity. All three tests also rely on the same formula to compute a test statistic.
Can you use both ANOVA and t-test?
While the t-test is used to compare the means between two groups, ANOVA is used to compare means between three or more groups. So for two groups, we can use both t-test and ANOVA and the results would be the same.
What is the best statistical test to compare two groups?
Choosing a statistical test
|Type of Data|
|Compare two unpaired groups||Unpaired t test||Fisher's test (chi-square for large samples)|
|Compare two paired groups||Paired t test||McNemar's test|
|Compare three or more unmatched groups||One-way ANOVA||Chi-square test|
|Compare three or more matched groups||Repeated-measures ANOVA||Cochrane Q**|