Table of Contents
- 1 What is the difference between dependent t test and independent t test?
- 2 What is a dependent t test?
- 3 How do you know if data is independent?
- 4 What is the difference between independent and dependent events Statistics quizlet?
- 5 What are dependent samples?
- 6 When to use an independent t test?
- 7 How do you calculate t test statistic?
What is the difference between dependent t test and independent t test?
Dependent samples are paired measurements for one set of items. Independent samples are measurements made on two different sets of items. When you conduct a hypothesis test using two random samples, you must choose the type of test based on whether the samples are dependent or independent.
What is a dependent t test?
The dependent t-test (also called the paired t-test or paired-samples t-test) compares the means of two related groups to determine whether there is a statistically significant difference between these means.
What is the difference between independent and dependent in statistics?
Dependent events influence the probability of other events – or their probability of occurring is affected by other events. Independent events do not affect one another and do not increase or decrease the probability of another event happening.
What does it mean for data to be independent?
Often, when reading a statistics book, you will see some variation on the phrase “independent data“. When we say data are independent, we mean that the data for different subjects do not depend on each other. When we say a variable is independent we mean that it does not depend on another variable for the same subject.
How do you know if data is independent?
Events A and B are independent if the equation P(A∩B) = P(A) · P(B) holds true. You can use the equation to check if events are independent; multiply the probabilities of the two events together to see if they equal the probability of them both happening together.
What is the difference between independent and dependent events Statistics quizlet?
Two events are independent when the occurrence of one event does not affect the probability of the occurrence of the other event. Two events are dependent when the occurrence of one event affects the probability of the occurrence of the other event.
How do you identify the dependent and independent variables?
An easy way to think of independent and dependent variables is, when you’re conducting an experiment, the independent variable is what you change, and the dependent variable is what changes because of that. You can also think of the independent variable as the cause and the dependent variable as the effect.
What is the difference between t-test and 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 are dependent samples?
In dependent samples, subjects in one group do provide information about subjects in other groups. The groups contain either the same set of subjects or different subjects that the analysts have paired meaningfully. Groups are frequently dependent because they contain the same subjects—that’s the most common example.
When to use an independent t test?
The independent-measures t-test (or independent t-test) is used when measures from the two samples being compared do not come in matched pairs. It is used when groups are independent and all people take only one test (typically a post-test).
What is an example of a dependent t test?
A dependent t-test is an example of a “within-subjects” or “repeated-measures” statistical test. This indicates that the same participants are tested more than once. Thus, in the dependent t-test, “related groups” indicates that the same participants are present in both groups.
When is it appropriate to use the paired difference t test?
The paired t test is generally used when measurements are taken from the same subject before and after some manipulation such as injection of a drug. For example, you can use a paired t test to determine the significance of a difference in blood pressure before and after administration of an experimental pressor substance.
How do you calculate t test statistic?
Calculate the T-statistic. Subtract the population mean from the sample mean: x-bar – μ. Divide s by the square root of n, the number of units in the sample: s ÷ √(n). Take the value you got from subtracting μ from x-bar and divide it by the value you got from dividing s by the square root of n: (x-bar – μ) ÷ (s ÷ √[n]).