What are the statistical treatment used in research?
In Data Analysis: Applying any statistical method — like regression or calculating a mean — to data. In Factor Analysis: Any combination of factor levels is called a treatment. In a Thesis or Experiment: A statistical treatment is a summary of the procedure, including statistical methods used.
What is the statistical method?
Definition. Statistical methods are mathematical formulas, models, and techniques that are used in statistical analysis of raw research data. The application of statistical methods extracts information from research data and provides different ways to assess the robustness of research outputs.
What is a 2 tailed t test?
In statistics, a two-tailed test is a method in which the critical area of a distribution is two-sided and tests whether a sample is greater or less than a range of values. If the sample being tested falls into either of the critical areas, the alternative hypothesis is accepted instead of the null hypothesis.
What do t test scores mean?
Higher values of the t-value, also called t-score, indicate that a large difference exists between the two sample sets. The smaller the t-value, the more similarity exists between the two sample sets. A large t-score indicates that the groups are different. A small t-score indicates that the groups are similar.
What is the null hypothesis for t test?
The null hypothesis (H_0) assumes that the difference between the true mean (\mu) and the comparison value (m_0) is equal to zero. The two-tailed alternative hypothesis (H_1) assumes that the difference between the true mean (\mu) and the comparison value (m_0) is not equal to zero.
Should I use a paired or unpaired t test?
Paired t-tests are considered more powerful than unpaired t-tests because using the same participants or item eliminates variation between the samples that could be caused by anything other than what’s being tested.
Are the two samples paired or independent?
There is no reason for pairing up individual cases in one group with individual cases in the other group. In fact, the number of cases in each of the two groups will typically not be the same. The groups (or samples) are independent of one another, thus the name independent samples.
When should you use a two-sample t-test?
The two-sample t-test (Snedecor and Cochran, 1989) is used to determine if two population means are equal. A common application is to test if a new process or treatment is superior to a current process or treatment. There are several variations on this test. The data may either be paired or not paired.
How do I report my paired t test results?
You will want to include three main things about the Paired Samples T-Test when communicating results to others.
- Test type and use. You want to tell your reader what type of analysis you conducted.
- Significant differences between conditions.
- Report your results in words that people can understand.
What are the two main assumptions underlying the repeated measures 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.
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.
What does an Anova test tell you?
The one-way analysis of variance (ANOVA) is used to determine whether there are any statistically significant differences between the means of two or more independent (unrelated) groups (although you tend to only see it used when there are a minimum of three, rather than two groups).