Using two Z tables makes life easier such that based on whether you want the know the area from the mean for a positive value or a negative value, you can use the respective Z score table. If you want to know the area between the mean and a negative value you will use the first table (1.1) shown above which is the left-hand/negative Z-table.

Z-Test is such a test statistic where we make use of the mean value and z score to determine the P-value. Z-Test compares the mean of two large samples taken from a population when the variance is known. Z-Test is usually used to conduct a hypothesis test when the sample size is greater than 30.

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Mapping Z scores on the Z table. Z score is also used to calculate the area associated with it and to find areas under the curve. Here we make use of the Z-Table or the standard normal table. By referring to this table, we can find the exact area to the left or right of a Z score in a standard normal distribution.

The Z score not only gives the measure of the deviation of an element but also indicates the exact position of the raw score with respect to the mean. Simply put, it is the measure of how many standard deviations below or above a raw element is from the mean.

Z Table or Standard Normal Table. A Z-Score allows us to calculate how much area that specific Z-Score is associated with and we can find out that exact area with help of ‘Z-Score Table’ also known as ‘Standard Normal Table’.

Creating a z-table from scratch does not better help us in any way in solving a problem and so we stick to using Z Score calculators available online or the Z Table available like the one on this website or in textbooks.

For this test, we create a Chi-Square table where each cell represents the frequency observed for each combination of categorical variables. Degrees of freedom can be defined as the number of cells in the Chi-Square table that can vary before the calculation of all other cells.

A hypothesis test will have two statements that are mutually exclusive. The sample data helps us to conclude which of the two assumed population parameters is true. The two mutually exclusive hypothesis are the null hypothesis and the alternate hypothesis.

In our example of plant growth, say that we took different types of plants ranging from flowers to vegetables and conducted the test. Now, we found out that the rose plant which is provided with 250 ml of water every day has a higher growth rate.