Z test is a statistical test that is conducted on data that approximately follows a normal distribution. The z test can be performed on one sample, two samples, or on proportions for hypothesis testing. It checks if the means of two large samples are different or not when the population variance is known. Show
A z test can further be classified into left-tailed, right-tailed, and two-tailed hypothesis tests depending upon the parameters of the data. In this article, we will learn more about the z test, its formula, the z test statistic, and how to perform the test for different types of data using examples.
What is Z Test?A z test is a test that is used to check if the means of two populations are different or not provided the data follows a normal distribution. For this purpose, the null hypothesis and the alternative hypothesis must be set up and the value of the z test statistic must be calculated. The decision criterion is based on the z critical value. Z Test DefinitionA z test is conducted on a population that follows a normal distribution with independent data points and has a sample size that is greater than or equal to 30. It is used to check whether the means of two populations are equal to each other when the population variance is known. The null hypothesis of a z test can be rejected if the z test statistic is statistically significant when compared with the critical value. Z Test FormulaThe z test formula compares the z statistic with the z critical value to test whether there is a difference in the means of two populations. In hypothesis testing, the z critical value divides the distribution graph into the acceptance and the rejection regions. If the test statistic falls in the rejection region then the null hypothesis can be rejected otherwise it cannot be rejected. The z test formula to set up the required hypothesis tests for a one sample and a two-sample z test are given below. One-Sample Z TestA one-sample z test is used to check if there is a difference between the sample mean and the population mean when the population standard deviation is known. The formula for the z test statistic is given as follows: z = \(\frac{\overline{x}-\mu}{\frac{\sigma}{\sqrt{n}}}\). \(\overline{x}\) is the sample mean, \(\mu\) is the population mean, \(\sigma\) is the population standard deviation and n is the sample size. The algorithm to set a one sample z test based on the z test statistic is given as follows: Left Tailed Test: Null Hypothesis: \(H_{0}\) : \(\mu = \mu_{0}\) Alternate Hypothesis: \(H_{1}\) : \(\mu < \mu_{0}\) Decision Criteria: If the z statistic < z critical value then reject the null hypothesis. Right Tailed Test: Null Hypothesis: \(H_{0}\) : \(\mu = \mu_{0}\) Alternate Hypothesis: \(H_{1}\) : \(\mu > \mu_{0}\) Decision Criteria: If the z statistic > z critical value then reject the null hypothesis. Two Tailed Test: Null Hypothesis: \(H_{0}\) : \(\mu = \mu_{0}\) Alternate Hypothesis: \(H_{1}\) : \(\mu \neq \mu_{0}\) Decision Criteria: If the z statistic > z critical value then reject the null hypothesis. Two Sample Z TestA two sample z test is used to check if there is a difference between the means of two samples. The z test statistic formula is given as follows: z = \(\frac{(\overline{x_{1}}-\overline{x_{2}})-(\mu_{1}-\mu_{2})}{\sqrt{\frac{\sigma_{1}^{2}}{n_{1}}+\frac{\sigma_{2}^{2}}{n_{2}}}}\). \(\overline{x_{1}}\), \(\mu_{1}\), \(\sigma_{1}^{2}\) are the sample mean, population mean and population variance respectively for the first sample. \(\overline{x_{2}}\), \(\mu_{2}\), \(\sigma_{2}^{2}\) are the sample mean, population mean and population variance respectively for the second sample. The two-sample z test can be set up in the same way as the one-sample test. However, this test will be used to compare the means of the two samples. For example, the null hypothesis is given as \(H_{0}\) : \(\mu_{1} = \mu_{2}\). Z Test for ProportionsA z test for proportions is used to check the difference in proportions. A z test can either be used for one proportion or two proportions. The formulas are given as follows. One Proportion Z TestA one proportion z test is used when there are two groups and compares the value of an observed proportion to a theoretical one. The z test statistic for a one proportion z test is given as follows: z = \(\frac{p-p_{0}}{\sqrt{\frac{p_{0}(1-p_{0})}{n}}}\). Here, p is the observed value of the proportion, \(p_{0}\) is the theoretical proportion value and n is the sample size. The null hypothesis is that the two proportions are the same while the alternative hypothesis is that they are not the same. Two Proportion Z TestA two proportion z test is conducted on two proportions to check if they are the same or not. The test statistic formula is given as follows: z =\(\frac{p_{1}-p_{2}-0}{\sqrt{p(1-p)\left ( \frac{1}{n_{1}} +\frac{1}{n_{2}}\right )}}\) where p = \(\frac{x_{1}+x_{2}}{n_{1}+n_{2}}\) \(p_{1}\) is the proportion of sample 1 with sample size \(n_{1}\) and \(x_{1}\) number of trials. \(p_{2}\) is the proportion of sample 2 with sample size \(n_{2}\) and \(x_{2}\) number of trials. How to Calculate Z Test Statistic?The most important step in calculating the z test statistic is to interpret the problem correctly. It is necessary to determine which tailed test needs to be conducted and what type of test does the z statistic belong to. Suppose a teacher claims that his section's students will score higher than his colleague's section. The mean score is 22.1 for 60 students belonging to his section with a standard deviation of 4.8. For his colleague's section, the mean score is 18.8 for 40 students and the standard deviation is 8.1. Test his claim at \(\alpha\) = 0.05. The steps to calculate the z test statistic are as follows:
Z Test vs T-TestBoth z test and t-test are univariate tests used on the means of two datasets. The differences between both tests are outlined in the table given below:
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Important Notes on Z Test
FAQs on Z TestWhat is a Z Test in Statistics?A z test in statistics is conducted on data that is normally distributed to test if the means of two datasets are equal. It can be performed when the sample size is greater than 30 and the population variance is known. What is a One-Sample Z Test?A one-sample z test is used when the population standard deviation is known, to compare the sample mean and the population mean. The z test statistic is given by the formula \(\frac{\overline{x}-\mu}{\frac{\sigma}{\sqrt{n}}}\). What is the Two-Sample Z Test Formula?The two sample z test is used when the means of two populations have to be compared. The z test formula is given as \(\frac{(\overline{x_{1}}-\overline{x_{2}})-(\mu_{1}-\mu_{2})}{\sqrt{\frac{\sigma_{1}^{2}}{n_{1}}+\frac{\sigma_{2}^{2}}{n_{2}}}}\). What is a One Proportion Z test?A one proportion z test is used to check if the value of the observed proportion is different from the value of the theoretical proportion. The z statistic is given by \(\frac{p-p_{0}}{\sqrt{\frac{p_{0}(1-p_{0})}{n}}}\). What is a Two Proportion Z Test?When the proportions of two samples have to be compared then the two proportion z test is used. The formula is given by \(\frac{p_{1}-p_{2}-0}{\sqrt{p(1-p)\left ( \frac{1}{n_{1}} +\frac{1}{n_{2}}\right )}}\). How Do You Find the Z Test?The steps to perform the z test are as follows:
What is the Difference Between the Z Test and the T-Test?A z test is used on large samples n ≥ 30 and normally distributed data while a t-test is used on small samples (n < 30) following a student t distribution. Both tests are used to check if the means of two datasets are the same. Can I use zThe Bottom Line
In particular, it tests whether two means are the same (the null hypothesis). A z-test can only be used if the population standard deviation is known and the sample size is 30 data points or larger.
How do you know if its tWhen to use Z-test vs T-test?. If the population standard deviation is known and the sample size is greater than 30, Z-test is recommended to be used.. If the population standard deviation is known, and the size of the sample is less than or equal to 30, T-test is recommended.. When the sample size is less than 30 which type of test is used?Z Test vs T-Test. What if my sample size is less than 30?For example, when we are comparing the means of two populations, if the sample size is less than 30, then we use the t-test. If the sample size is greater than 30, then we use the z-test.
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