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How do you use a t test to compare two groups?
Jan 31, 2020 · If the groups come from a single population (e.g. measuring before and after an experimental treatment), perform a paired t-test. If the groups come from two different populations (e.g. two different species, or people from two separate cities), perform a two-sample t-test (a.k.a. independent t-test). If there is one group being compared against a standard value …
What is a t test used for in research?
Nov 20, 2018 · Randomly sampling will be used to select 120 patrol officers from the Duty List at each site; then random sampling will be used to place those 120 into three respective groups: treatment group – given automatic body cameras (N=40), control group A – given traditional body cameras (N=40), and control group B – given no cameras.
What is the difference between paired t test and independent t test?
An independent t-test was run on a sample of 30 heavy smokers to determine if there were differences in cigarette consumption based on treatment type, consisting of a placebo (the control group) and nicotine patches (the treatment group).
What is an independent t-test used for?
Mar 11, 2020 · A two sample t-test was conducted on 24 cars to determine if a new fuel treatment lead to a difference in mean miles per gallon. Each group contained 12 cars. Results showed that the mean mpg was not different between the two groups (t = -1.428 w/ df=22, p = .1673) at a significance level of 0.05.
What is the t-test for between groups?
The between groups t-test is used when we have a continuous dependent variable and we are interested in comparing two groups. An example might be if there is experiment with an experimental and control group, or perhaps a comparison between two non-experimental groups like women and men.
When should you use the t-test?
When to use a t-test A t-test can only be used when comparing the means of two groups (a.k.a. pairwise comparison). If you want to compare more than two groups, or if you want to do multiple pairwise comparisons, use an ANOVA test or a post-hoc test.Jan 31, 2020
What test is used to compare 3 groups?
Choosing a statistical testType of DataCompare two paired groupsPaired t testMcNemar's testCompare three or more unmatched groupsOne-way ANOVAChi-square testCompare three or more matched groupsRepeated-measures ANOVACochrane Q**Quantify association between two variablesPearson correlationContingency coefficients**6 more rows•Mar 23, 2012
Can I use t-test to compare 3 groups?
for comparing three means you can use Both ANOVA and t test. t test is mainly used to compare two group means. for comparing more than two group means ANOVA is used. ANOVA works for large sample, normal distribution, equal variances.
What t-test type compares the means for two groups?
Independent Samples t TestThe Independent Samples t Test compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different. The Independent Samples t Test is a parametric test. This test is also known as: Independent t Test.Apr 4, 2022
What are the three types of t tests?
There are three main types of t-test:An Independent Samples t-test compares the means for two groups.A Paired sample t-test compares means from the same group at different times (say, one year apart).A One sample t-test tests the mean of a single group against a known mean.
Why can't you use t-test to compare three or more means?
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. This error is usually 5%. By running two t-tests on the same data you will have increased your chance of "making a mistake" to 10%.
What is a two-sample t-test used for?
The two-sample t-test (also known as the independent samples t-test) is a method used to test whether the unknown population means of two groups are equal or not.
Is a paired t-test two tailed?
The software shows results for a two-sided test (Prob > |t|) and for one-sided tests. The two-sided test is what we want. Our null hypothesis is that the mean difference between the paired exam scores is zero. Our alternative hypothesis is that the mean difference is not equal to zero.
Can't-test be used for more than 2 groups?
The t statistic is the ratio of mean difference and standard errors of the mean difference. Even when more than two groups are compared, some researchers erroneously apply the t test by implementing multiple t tests on multiple pairs of means.Jan 20, 2014
How do you compare the differences between two groups?
A common way to approach that question is by performing a statistical analysis. The two most widely used statistical techniques for comparing two groups, where the measurements of the groups are normally distributed, are the Independent Group t-test and the Paired t-test.
What test is used to assess differences between one group that has completed two conditions?
A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. The t-test is one of many tests used for the purpose of hypothesis testing in statistics. Calculating a t-test requires three key data values.
What is a t-test?
A t-test is a statistical test that compares the means of two samples . It is used in hypothesis testing , with a null hypothesis that the diff...
What does a t-test measure?
A t-test measures the difference in group means divided by the pooled standard error of the two group means. In this way, it calculates a numbe...
Which t-test should I use?
Your choice of t-test depends on whether you are studying one group or two groups, and whether you care about the direction of the difference in...
What is the difference between a one-sample t-test and a paired t-test?
A one-sample t-test is used to compare a single population to a standard value (for example, to determine whether the average lifespan of a speci...
Can I use a t-test to measure the difference among several groups?
A t-test should not be used to measure differences among more than two groups, because the error structure for a t-test will underestimate the ac...
What is the treatment group?
The treatment group (also called the experimental group) receives the treatment whose effect the researcher is interested in. The control group receives either no treatment, a standard treatment whose effect is already known, or a placebo (a fake treatment). The treatment is any independent variable manipulated by the experimenters, ...
What happens if your control group differs from the treatment group?
If your control group differs from the treatment group in ways that you haven’t accounted for, your results may reflect the interference of confounding variables instead of your independent variable.
Why are control groups important?
Importance of control groups. Control groups help ensure the internal validity of your research. You might see a difference over time in your dependent variable in your treatment group. However, without a control group, it is difficult to know whether the change has arisen from the treatment.
What is a control group in science?
Revised on April 19, 2021. In a scientific study, a control group is used to establish a cause-and-effect relationship by isolating the effect of an independent variable. Researchers change the independent variable in the treatment group ...
How to reduce confounding variables?
There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization. In restriction, you restrict your sample by only including certain subjects that have the same values of potential confounding variables.
What is treatment in research?
The treatment is any independent variable manipulated by the experimenters, and its exact form depends on the type of research being performed. In a medical trial, it might be a new drug or therapy. In public policy studies, it could be a new social policy that some receive and not others.
What is a confounding variable?
A confounding variable, also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship. A confounding variable is related to both the supposed cause and the supposed effect of the study.
What is an independent t-test?
The independent t-test, also referred to as an independent-samples t-test, independent-measures t-test or unpaired t-test, is used to determine whether the mean of a dependent variable (e.g., weight, anxiety level, salary, reaction time, etc.) is the same in two unrelated, independent groups (e.g., males vs females, employed vs unemployed, under 21 year olds vs those 21 years and older, etc.). Specifically, you use an independent t-test to determine whether the mean difference between two groups is statistically significantly different to zero.
How many assumptions are there in a t-test?
There are six "assumptions" that underpin the independent t-test. If any of these six assumptions are not met, you cannot analyse your data using an independent t-test because you will not get a valid result.
How many steps are required to run a t-test in Stata 12?
The three steps required to run an independent t-test in Stata 12 – known as a two-group mean-comparison test in Stata 12 – are shown below. The same procedure requires four steps in Stata 13 and this is shown further down: Stata.
What are some examples of independent variables?
Examples of such independent variables include gender (2 groups: male or female), treatment type (2 groups: medication or no medication), educational level (2 groups: undergraduate or postgraduate), religious (2 groups: yes or no), and so forth.
What is the assumption of independence of observations?
Assumption #3: You should have independence of observations, which means that there is no relationship between the observations in each group or between the groups themselves. For example, there must be different participants in each group with no participant being in more than one group.
What is an ANOVA test?
An ANOVA tests the null hypothesis that there is no difference among the mean values for the different treatment groups. Although it is possible to conduct an ANOVA by hand, no one in their right mind having access to computer software would do so. Setting up an ANOVA using RStudio is quite easy.
What is the purpose of ANOVA?
The fundamental principle in ANOVA is to determine how many times greater the variability due to the treatment is than the variability that we cannot explain.
What is the goal of experimental science?
We have seen previously that a major goal of experimental science is to detect differences between measurements that have resulted from different treatments. Early on we learned that it is not possible to assess these differences based on a single measurement of each treatment. Without knowing how much variation existed within a treatment, we could not know if the difference between treatments was significantly large. The simplest and first formal statistical test we learned about, the t -test of means, provided a mathematical way of comparing the size of differences of means relative to the variability in the samples used to calculate those means.
What is mean square in statistics?
The mean square is analogous to the variance (i.e. the square of the standard deviation) of a distribution. Thus a large mean square represents a large variance, and vice versa. The F ratio is simply the model mean square divided by the residuals mean square.
What is a t-test?
A t-test is used to determine whether or not there is a statistically significant difference between the means of two groups. There are two types of t-tests: 1. Independent samples t-test. This is used when we wish to compare the difference between the means of two groups and the groups are completely independent of each other.
How to determine if a t-test is valid?
For a t-test to produce valid results, the following assumptions should be met: 1 Random: A random sample or random experiment should be used to collect data for both samples. 2 Normal: The sampling distribution is normal or approximately normal.
What is a two way ANOVA?
Two-way ANOVA: Used to test whether or not there is a statistically significant difference between the means of three or more groups when the groups can be split on two factors. Example: You want to determine if level of exercise (no exercise, light exercise, intense exercise) and gender (male, female) impact weight loss.
What is the difference between a t-test and an ANOVA?
The main difference between a t-test and an ANOVA is in how the two tests calculate their test statistic to determine if there is a statistically significant difference between groups.
What is an ANOVA?
An ANOVA (analysis of variance) is used to determine whether or not there is a statistically significant difference between the means of three or more groups. The most commonly used ANOVA tests in practice are the one-way ANOVA and the two-way ANOVA:
Most recent answer
I agree with Daniel, a plot needs to show details about the dataset, not just means. My suggestion was to plot all the data (i.e., every data point); examples of this are included in the references I posted above.
Popular Answers (1)
Based on what you've explained, you're not actually comparing groups, you're doing within-participant comparisons. Therefore, methods typically used for within-participant comparisons (e.g. paired/dependent samples t-tests, repeated measures ANOVA, etc.) would normally be appropriate.
All Answers (16)
Not completely sure if I understand your question, but if you want to compare your 4 treatments with a control, you can use Dunnett's procedure. It's a procedure to do pairwise comparisons between (active) treatments with a control treatment. The method requires equal sample sizes.
Control Groups in Experiments
- Control groups are essential to experimental design. When researchers are interested in the impact of a new treatment, they randomly divide their study participants into at least two groups: 1. The treatment group (also called the experimental group) receives the treatment whose effect the researcher is interested in. 2. The control groupreceives e...
Control Groups in Non-Experimental Research
- Although control groups are more common in experimental research, they can be used in other types of research too. Researchers generally rely on non-experimental control groups in two cases: quasi-experimental or matching design.
Importance of Control Groups
- Control groups help ensure the internal validityof your research. You might see a difference over time in your dependent variable in your treatment group. However, without a control group, it is difficult to know whether the change has arisen from the treatment. It is possible that the change is due to some other variables. If you use a control group that is identical in every other way to t…