2021년 2월 17일 (수) 08:10에 Pythagoras0님의 편집

2021-02-17T08:10:00Z

Pythagoras0: /* 메타데이터 */ 새 문단

2020-12-26T12:18:32Z

메타데이터: 새 문단

Pythagoras0: /* 노트 */ 새 문단

2020-12-21T10:18:59Z

노트: 새 문단

새 문서

== 노트 ==

===위키데이터===
* ID : [https://www.wikidata.org/wiki/Q309479 Q309479]
===말뭉치===
# A paired t test (also called a correlated pairs t-test, a paired samples t test or dependent samples t test) is where you run a t test on dependent samples.<ref name="ref_b5ccdf1f">[https://www.statisticshowto.com/probability-and-statistics/t-test/ T Test (Student’s T-Test): Definition and Examples]</ref>
# Choose the paired t-test if you have two measurements on the same item, person or thing.<ref name="ref_b5ccdf1f" />
# With a “regular” two sample t test, you’re comparing the means for two different samples.<ref name="ref_b5ccdf1f" />
# With the paired t test, the null hypothesis is that the pairwise difference between the two tests is equal (H 0 : µ d = 0).<ref name="ref_b5ccdf1f" />
# A t test compares the means of two groups.<ref name="ref_4251755a">[https://www.graphpad.com/quickcalcs/ttest1.cfm GraphPad QuickCalcs: t test calculator]</ref>
# The t test compares one variable (perhaps blood pressure) between two groups.<ref name="ref_4251755a" />
# Finally, don't confuse a t test with analyses of a contingency table (Fishers or chi-square test).<ref name="ref_4251755a" />
# Use a t test to compare a continuous variable (e.g., blood pressure, weight or enzyme activity).<ref name="ref_4251755a" />
# In 1908 William Sealy Gosset, an Englishman publishing under the pseudonym Student, developed the t-test and t distribution.<ref name="ref_da700df0">[https://www.britannica.com/science/Students-t-test Student’s t-test | Definition, Formula, & Example]</ref>
# Some modification of the procedure of dividing the difference by its standard error is needed, and the technique to use is the t test.<ref name="ref_daf21531">[https://www.bmj.com/about-bmj/resources-readers/publications/statistics-square-one/7-t-tests 7. The t tests]</ref>
# Its foundations were laid by WS Gosset, writing under the pseudonym “Student” so that it is sometimes known as Student’s t test.<ref name="ref_daf21531" />
# The unequal variance t test tends to be less powerful than the usual t test if the variances are in fact the same, since it uses fewer assumptions.<ref name="ref_daf21531" />
# If a log transformation is successful use the usual t test on the logged data.<ref name="ref_daf21531" />
# First consider if the data meet the requirements for an unpaired t-test.<ref name="ref_439631e4">[https://www.sciencedirect.com/topics/medicine-and-dentistry/student-t-test Student T Test - an overview]</ref>
# Exclude this measurement and repeat the unpaired t-test with 9 in the raw group and 10 in the roasted group.<ref name="ref_439631e4" />
# This function uses the Student's t-test to test the null hypothesis that the sample means are from the same population (i.e. H0: ave1=ave2).<ref name="ref_a80f75eb">[https://www.ncl.ucar.edu/Document/Functions/Built-in/ttest.shtml ttest]</ref>
# A t-test is the most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic were known.<ref name="ref_5a9327af">[https://en.wikipedia.org/wiki/Student%27s_t-test Student's t-test]</ref>
# Hence a second version of the etymology of the term Student is that Guinness did not want their competitors to know that they were using the t-test to determine the quality of raw material.<ref name="ref_5a9327af" />
# Gosset devised the t-test as an economical way to monitor the quality of stout.<ref name="ref_5a9327af" />
# The independent samples t-test is used when two separate sets of independent and identically distributed samples are obtained, one from each of the two populations being compared.<ref name="ref_5a9327af" />
# 'Student's' t Test (For Independent Samples) Use this test to compare two small sets of quantitative data when samples are collected independently of one another.<ref name="ref_c71fe604">[https://www.ruf.rice.edu/~bioslabs/tools/stats/ttest.html 'Student's' t Test (For Independent Samples)]</ref>
# Use of a paired t test, to which some statistics programs unfortunately default, requires nonrandom sampling (see below).<ref name="ref_c71fe604" />
# Here's a simple check to determine if the paired t test can apply - if one sample can have a different number of data points from the other, then the paired t test cannot apply.<ref name="ref_c71fe604" />
# Examples 'Student's' t Test is one of the most commonly used techniques for testing a hypothesis on the basis of a difference between sample means.<ref name="ref_c71fe604" />
# The t-Test A t-test is any statistical hypothesis test in which the test statistic follows a Student’s t-distribution if the null hypothesis is supported.<ref name="ref_2e8e4656">[https://courses.lumenlearning.com/boundless-statistics/chapter/the-t-test/ Boundless Statistics]</ref>
# The t-test is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic were known.<ref name="ref_2e8e4656" />
# A t-test is any statistical hypothesis test in which the test statistic follows a Student’s t-distribution if the null hypothesis is supported.<ref name="ref_2e8e4656" />
# Gosset devised the t-test as a cheap way to monitor the quality of stout.<ref name="ref_2e8e4656" />
# t-test definition Student t test is a statistical test which is widely used to compare the mean of two groups of samples.<ref name="ref_73848cbb">[http://www.sthda.com/english/wiki/t-test-formula t test formula]</ref>
# The paired t-test, used to compare the means between two related groups of samples.<ref name="ref_73848cbb" />
# The aim of this article is to describe the different t test formula.<ref name="ref_73848cbb" />
# Student’s t-test is a parametric test as the formula depends on the mean and the standard deviation of the data being compared.<ref name="ref_73848cbb" />
# In the case of the Student’s t-test, the mean is used to compare the two samples.<ref name="ref_0016c2b8">[https://www.statsandr.com/blog/student-s-t-test-in-r-and-by-hand-how-to-compare-two-groups-under-different-scenarios/ Student's t-test in R and by hand: how to compare two groups under different scenarios]</ref>
# In this article, I will first detail step by step how to perform all versions of the Student’s t-test for independent and paired samples by hand.<ref name="ref_0016c2b8" />
# Note that the aim of this article is to show how to compute the Student’s t-test by hand and in R, so we refrain from testing the assumptions and we assume all of them are met for this exercise.<ref name="ref_0016c2b8" />
# If the t-stat lies in the rejection region (determined thanks to the critical value and the direction of the test), we reject the null hypothesis, otherwise we do not reject the null hypothesis.<ref name="ref_0016c2b8" />
# A very useful test for such applications is the t-test (sometimes referred to as Student's t-test after the statistician who developed the test).<ref name="ref_5691d643">[https://www.colby.edu/biology/BI17x/t_test.html Student's t-test]</ref>
# Student developed the t-test to allow us to assign a probability level to describe the likelihood that the null hypothesis is true.<ref name="ref_5691d643" />
# Now we can consult a table of critical values of t, analagous to searching for the critical values of the chi-squared test.<ref name="ref_5691d643" />
# A t-test is a statistical test that is used to compare the means of two groups.<ref name="ref_5a318050">[https://www.scribbr.com/statistics/t-test/ An introduction to t-tests]</ref>
# You can test the difference between these two groups using a t-test.<ref name="ref_5a318050" />
# A t-test can only be used when comparing the means of two groups (a.k.a. pairwise comparison).<ref name="ref_5a318050" />
# The t-test is a parametric test of difference, meaning that it makes the same assumptions about your data as other parametric tests.<ref name="ref_5a318050" />
# 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.<ref name="ref_86f759eb">[https://www.investopedia.com/terms/t/t-test.asp T-Test Definition]</ref>
# A t-test looks at the t-statistic, the t-distribution values, and the degrees of freedom to determine the statistical significance.<ref name="ref_86f759eb" />
# 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.<ref name="ref_86f759eb" />
# Mathematically, the t-test takes a sample from each of the two sets and establishes the problem statement by assuming a null hypothesis that the two means are equal.<ref name="ref_86f759eb" />
# Independent sample t-tests are commonly used in the psychological literature to statistically test differences between means.<ref name="ref_90d7dfcb">[https://www.rips-irsp.com/articles/10.5334/irsp.82/ Why Psychologists Should by Default Use Welch’s t-test Instead of Student’s t-test]</ref>
# There are different types of t-tests, such as Student’s t-test, Welch’s t-test, Yuen’s t-test, and a bootstrapped t-test.<ref name="ref_90d7dfcb" />
# Student’s t-test is the default method to compare two groups in psychology.<ref name="ref_90d7dfcb" />
# When performing a t-test, several software packages (i.e., R and Minitab) present Welch’s t-test by default.<ref name="ref_90d7dfcb" />
# To explain, let’s use the one-sample t-test.<ref name="ref_ec88f2b9">[https://www.jmp.com/en_ch/statistics-knowledge-portal/t-test.html The t-Test]</ref>
# paired a logical indicating whether you want a paired t-test.<ref name="ref_12858b86">[https://stat.ethz.ch/R-manual/R-devel/library/stats/html/t.test.html R: Student's t-Test]</ref>
# method a character string indicating what type of t-test was performed.<ref name="ref_12858b86" />
# It will function as the independent variable in this T test.<ref name="ref_d031e53a">[https://libguides.library.kent.edu/spss/independentttest LibGuides at Kent State University]</ref>
# Before running the Independent Samples t Test, it is a good idea to look at descriptive statistics and graphs to get an idea of what to expect.<ref name="ref_d031e53a" />
# Click OK to run the Independent Samples t Test.<ref name="ref_d031e53a" />
# The second section, Independent Samples Test, displays the results most relevant to the Independent Samples t Test.<ref name="ref_d031e53a" />
# The single-sample t-test compares the mean of the sample to a given number (which you supply).<ref name="ref_7ada1ddd">[https://stats.idre.ucla.edu/stata/output/t-test/ T-test | Stata Annotated Output]</ref>
# The independent samples t-test compares the difference in the means from the two groups to a given value (usually 0).<ref name="ref_7ada1ddd" />
# If the p-value associated with the t-test is small (0.05 is often used as the threshold), there is evidence that the mean is different from the hypothesized value.<ref name="ref_7ada1ddd" />
# A paired (or “dependent”) t-test is used when the observations are not independent of one another.<ref name="ref_7ada1ddd" />
# The sample groups in a student t test are both drawn randomly from the same population.<ref name="ref_62e9460e">[https://radiopaedia.org/articles/student-t-test-1 Radiology Reference Article]</ref>
# However, the t-test is described as a robust test with respect to the assumption of normality.<ref name="ref_082b7ffd">[https://statistics.laerd.com/statistical-guides/independent-t-test-statistical-guide.php Independent T-Test - An introduction to when to use this test and what are the variables required]</ref>
# The independent t-test assumes the variances of the two groups you are measuring are equal in the population.<ref name="ref_082b7ffd" />
# The assumption of homogeneity of variance can be tested using Levene's Test of Equality of Variances, which is produced in SPSS Statistics when running the independent t-test procedure.<ref name="ref_082b7ffd" />
# This article describes the independent Student T-test, which is used to compare the means of two independent groups.<ref name="ref_b006682e">[https://www.datanovia.com/en/lessons/types-of-t-test/unpaired-t-test/students-t-test/ Student's T-Test : Excellent Reference You Will Love]</ref>
# This test is also referred as Students t-test, Student’s t-test and equal variance t-test.<ref name="ref_b006682e" />
# the Welch’s t-test, which is less restrictive compared to the original Student’s test.<ref name="ref_b006682e" />
# Note that, the Welch t-test is considered as the safer one.<ref name="ref_b006682e" />
# Before using this type of test it is essential to plot the sample data from the two samples and make sure that it has a reasonably normal distribution, or the student's t test will not be suitable.<ref name="ref_41559c62">[https://explorable.com/students-t-test Testing Hypotheses]</ref>
# If the distribution is skewed, then the student's t test is likely to throw up misleading results.<ref name="ref_41559c62" />
# The student's t test can let you know if there is a significant difference in the means of the two sample groups and disprove the null hypothesis.<ref name="ref_41559c62" />
# “The Student’s t Test is used to compare the mean of two normally distributed samples, preferably of equal size and variance.<ref name="ref_8166715f">[https://www.openanesthesia.org/students_t_test/ Student’s t Test]</ref>
# More specifically, the Student’s t Test gives you a probabilistic estimate of the likelihood that your samples were randomly selected from the same population, i.e. that the Null Hypothesis is true.<ref name="ref_8166715f" />
# t Test in terms of “signal to noise” ratios, the “signal” is the difference between the mean of two samples (similar to the Z test).<ref name="ref_8166715f" />
# Remember, the t Test assumes normally distributed data.<ref name="ref_8166715f" />
# When using a t-test of significance it is assumed that the observations come from a population which follows a Normal distribution.<ref name="ref_722debc3">[https://serc.carleton.edu/introgeo/teachingwdata/Ttest.html t-test]</ref>
# The paired t test provides an hypothesis test of the difference between population means for a pair of random samples whose differences are approximately normally distributed.<ref name="ref_2bde9159">[https://www.statsdirect.com/help/parametric_methods/paired_t.htm Paired Student t Test]</ref>
# StatsDirect displays these limits with an agreement plot if you check the agreement box before a paired t test runs.<ref name="ref_2bde9159" />
# To run this example, open the test workbook using the open file function of the file menu then choose paired t test from the parametric methods section of the analysis menu.<ref name="ref_2bde9159" />
# Student t-test would be used to compare two population means using samples from each.<ref name="ref_ab02562b">[https://sixsigmastudyguide.com/students-t-distribution/ Student’s T Distribution, Student’s T test]</ref>
# When the difference between two population averages is being investigated, a t test is used.<ref name="ref_9be195f6">[https://researchbasics.education.uconn.edu/t-test/ Educational Research Basics by Del Siegle]</ref>
# In other words, a t test is used when we wish to compare two means (the scores must be measured on an interval or ratio measurement scale).<ref name="ref_9be195f6" />
# We would use a t test if we wished to compare the reading achievement of boys and girls.<ref name="ref_9be195f6" />
# The test statistic that a t test produces is a t-value.<ref name="ref_9be195f6" />
# The t-test also called "student's t-test" and follows the t distribution.<ref name="ref_a4bcb7de">[https://develve.net/t-test.html t-test]</ref>
# Ifis selected and one of thecontains 1 value the 1 sample t-test is calculated.<ref name="ref_a4bcb7de" />
# To use the 1 sample t-test test first unselect "non normal distributed" when the box is selected theis calculated.<ref name="ref_a4bcb7de" />
# Then selectIfis selected the 2 sample t-test is calculated between this column, and the, if this column and the comparing column contains more than 1 value.<ref name="ref_a4bcb7de" />
# The one-sample Student's t-Test determines whether or not the mean of a sample taken from a normally distributed population is consistent with the hypothetical value for a given confidence level.<ref name="ref_b868af72">[https://www.originlab.com/doc/Origin-Help/tTest-OneSample One-Sample T-Test]</ref>
# By choosing a one- or two-tailed t-test, you can test how likely it is that the sample mean is greater than, less than, or equal to the true population mean.<ref name="ref_b868af72" />
# Note that the one-sample t-test is appropriate when the standard deviation of the entire population is unknown.<ref name="ref_b868af72" />
# Upon clicking OK, a report table sheet is generated to show the degrees of freedom, t statistics, the associated p-value, and the test conclusion.<ref name="ref_b868af72" />
===소스===
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← 이전 판		2020년 12월 26일 (토) 12:18 판
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T-test - 편집 역사

2021년 2월 17일 (수) 08:10에 Pythagoras0님의 편집

Pythagoras0: /* 메타데이터 */ 새 문단

Pythagoras0: /* 노트 */ 새 문단