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P value в excel

P-Value in Excel

P-value is used in Co-relation and regression analysis in excel which helps us to identify whether the result obtained is feasible or not and which data set from result to work with the value of P-value ranges from 0 to 1, there is no inbuilt method in excel to find out P-value of a given data set instead we use other functions such as Chi function.

P-Value in Excel (Table of Contents)

Excel P-Value

P-Value is nothing but the probability value expressed in percentage value in hypothesis testing to support or reject the null hypothesis. P Value or Probability Value is a popular concept in the statistical world. All the aspiring analysts should know about the P Value and its purpose in data science. A frequency of the data points called as the hypothetical frequency and observed significance level for the test hypothesis.

  • P value is denoted by decimal points but it is always a good thing to tell the result of the P value in percentage instead of decimal points. Telling 5% is always better than telling the decimal points 0.05.
  • In the test conducted to find the P-Value, if the P value is smaller then, the stronger evidence against the null hypothesis and your data is more important or significant. If the P value is higher then, there is weak evidence against the null hypothesis. So, by running a hypothesis test and finding P value we can actually understand the significance of finding.

How to Calculate the P-Value in T-Test in Excel?

Below are the examples to Calculate P Value in Excel T-Test.

P Value Excel T-Test Example #1

In excel we can find the P-Value easily. By running T-Test in excel we can actually arrive at the statement whether the null hypothesis is TRUE or FALSE. Look at the below example to understand the concept practically.

Assume you are supplied with weight loss process through diet data and below is the data available to you to test the null hypothesis.

Step 1: First thing we need to do is calculate the difference between before diet and after diet.

The output is given below:

Drag the Formula to rest of cells.

Step 2: Now go to the Data tab and under the data, tab click on Data Analysis.

Excel P-Value

Excel P-Value (Table of Content)

P-Value in Excel

  • P-Values in excel can be called probability values, it’s used to understand the statical significance of a finding.
  • The P-Value is used to test the validity of the Null Hypothesis. If the null hypothesis is considered improbable according to the P-Value then it leads us to believe that the alternative hypothesis might be true. Basically, it allows us whether the provided results been caused by chance or these demonstrate that we are testing two unrelated things. So P-Value is an investigator and not a Judge.
  • A P-Value is a number between 0 and 1 but it’s easier to think about them in percentages (i.e. for Pvalue of 0.05 is 5%. Smaller Pvalue leads to the rejection of the null hypothesis.
  • Finding P-Value for correlation in excel is a relatively straight forward process, but there is not a single function for the task, we will see the example for the same too.
  • The formula to calculate the P-Value is TDIST(x, deg_freedom, tails)

Excel functions, formula, charts, formatting creating excel dashboard & others

Null hypothesis:

  • When we are comparing two things with each other then the null hypothesis is the assumption that there is no relation between two things.
  • Before comparing two things with each other we must have to prove that there is some relation exists between these two.
  • When a P-Value rejects the null hypothesis, we can say that it has good chances for both things which we are comparing has some relationship with each other.
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How to Calculate P-Value in Excel?

Let’s understand how to calculate P-Value in Excel by using some examples.

P-Value in Excel – Example #1

In this example, we will calculate P-Value in Excel for the given data.

  • As per the Screenshot, we can see below, we have collected data of some cricketers against the runs they have made in a particular series.

  • Now, for this we need another tail, we have to get the expected runs to had to be scored by each batsman.
  • For the expected runs column we will find the average runs for each player by dividing our sum of counts by the sum of runs as follows.

  • Here we have found the expected value by dividing our sum of counts by the sum of runs. Basically average and in our case, it’s 63.57.
  • As we can see from the table we have added the column for expected runs by dragging the formula used in cell C3.

Now to find P-Value for this particular expression, the formula for that is TDIST(x, deg_freedom, tails).

  • x = the range of our data, which are runs
  • deg_freedom = range of the data of our expected values.
  • tails = 2, as we want the answer for two tails.

  • From the above image, we can see that the results we got is nearly 0.
  • So for this example, we can say that we have strong ev >

  • Here as we can see the results, if we can see in percentages it’s 27.2%.

Similarly, you can find the P-Values for by this method when values of x, n, and tails are provided.

P-Value in Excel – Example #3

Here we will see how to calculate P-Value in excel for Correlation.

  • While in the excel there isn’t a formula which gives a direct value of correlation’s associated P-Value.
  • So we have to get P-Value from correlation, correlation is r for P-Value as we have discussed before, to find P-Valuepvalue we have to find after getting correlation for the given values.
  • To find correlation the formula is CORREL(array1,array2)

  • From the correlation’s equation, we will find test statistics r. We can find t for P-Value.
  • To derive t from r the formula t= (r*sqrt(n-2))/(sqrt(1-r^2)
  • Now, suppose n (no. Of observation) is 10 and r=0.5

  • From the above image, we have found the t = 1.6329…
  • Now to assess the significance value associated with t, simply use TDIST function.

=t.dist.2t(t, degree_freedom)

  • So the P-Value we have found for given correlation is 0.1411.
  • From this method, we can find the P-Value from the correlation, but after finding the correlation we have to find t and then after we will be able to find the P-Value.

A/B testing:

  • A/B testing is rather a regular example than an excel example of a P-Value.
  • Here we are taking an example of a product launch event organized by a telecom company:
  • We are going to categorize the data or engaging people with historical data and observed data. Historical data in the sense of the expected people as per the past launch events.

Test: 1 Expected Data:

Total Visitors: 5,000

Test: 2 Observed Data:

Total Visitors: 7,000

  • Now to find x 2 we have to use chi squared formula, in mathematical its addition of (observed data – Expected) 2 / Expected
  • For our observations its x 2 = 1000

  • Now if we check our result with chi-squared chart and just run through, our chi-squared score of 1000 with a degree of freedom 1.
  • As per the above chi-squared table above, and the idea is we’ll move from left to right until we find a score corresponds to our scores. Our approximate P-Value is then the P value at the top of the table aligned with your column.
  • For our test the score is very much high than the highest value in the given table of 10.827. So we can assume that P-Value for our test is less than 0.001 at least.
  • If we run our score through GraphPad, we will see it’s value is about less than 0.00001.

Things To Remember About P-Value in Excel

  • P-Value involves measuring, comparing, testing all things that constitute research.
  • P-Values are not the be all research, it only helps you to understand the probability of your results existing through chance against through changed conditions.
  • It doesn’t really tell you about causes, magnitude or to identify variables.

Recommended Articles

This has been a guide to P-Value in Excel. Here we discussed How to calculate P-Value in Excel along with practical examples and downloadable excel template. You can also go through our other suggested articles –

How to Calculate P Value in Excel

Written by co-founder Kasper Langmann, Microsoft Office Specialist.

The p-value, short for probability value , is an important concept in statistical hypothesis testing.

Its use in hypothesis testing is common in many fields like finance, physics, economics, psychology, and many others.

Knowing how to compute the probability value using Excel is a great time-saver.

In this article, we’ll show you 2 easy ways you can calculate the p-value in Excel.

Let’s get started!

*This tutorial is for Excel 2019 for Windows. Got a different version? No problem, you can still follow the exact same steps.

Table of Content

The concept of P Value

Basically, the p-value is used in hypothesis testing to quantify the >.

It’s a value that can be expressed in percentage or decimal to support or reject the null hypothesis.

In Excel, the p-value is expressed in decimal.

But in reporting, try to use the percentage form (multiply the decimal form by 100) as some people prefer hearing it that way like it’s a part of a whole.

As for the results:

As stated earlier, there are two ways to get the p-value in Excel:

  1. t-Test tool in the analysis toolpak
  2. The ‘T.TEST’ function

For this tutorial, we’ll be using the gym program data set shown below and compute the p-value:

Get your FREE exercise file

Before you start:

Throughout this guide, you need a data set to practice.

I’ve included one for you (for free).

Download it right below!

Download the FREE Exercise File

The t-Test tool in the Analysis ToolPak

To use the t-Test tool in the Analysis ToolPak, you have to load the toolpak first in Excel.

  • Click ‘File’ from the tab list
  • Click ‘Options’ on the bottom of the left-hand sidebar
  • Click ‘Add-ins’ on the left-hand sidebar of the window
  • On the bottom part, make sure that ‘Excel Add-ins’ is selected
  • Then, press ‘Go’
  • On the next window, check the ‘Analysis ToolPak’
  • Click ‘OK’

Now that the toolpak is loaded, click ‘Data’ from the tab list.

On the ‘Analysis’ group, click the ‘Data Analysis’ icon .

On the window, select ‘t-Test: Paired Two Sample for Means’ . Then, click ‘OK’ .

Another window will open with the following options:

  • ‘Variable 1 Range’ – the cell range of the ‘before’ data (‘Weight’)
  • ‘Variable 2 Range’ – the cell range of the ‘after’ data (‘Result’)
  • ‘Hypothesized Mean Difference’ – the hypothesized mean difference; can be left blank
  • ‘Labels’ – if labels were included in the ranges
  • ‘Alpha’ – common alpha values are 0.05 and 0.01
  • ‘Output options’ – determine where the results will be placed

As an example, let’s supply the tool with the following variables:

  • ‘Variable 1 Range’ – $B$2:$B$12
  • ‘Variable 2 Range’ – $C$2:$C$12
  • ‘Labels’ – Check
  • ‘Alpha’ – 0.05
  • ‘Output options’ – ‘Output Range: $F$2’

The results will be displayed on the range provided:

On the results, we can see that the p-value with the one-tail test is 0.0063 or 0.63% and the p-value with the two-tail test is 0.0127 or 1.27%.

Both results show that the p-value is lower than 5% , which means the null hypothesis is significant .

How To : Find a P-Value with Excel

So you need to find the p-value for your hypothesis test. To do so, employ the spreadsheet program Microsoft Excel. Using a simple formula, you can easily determine the p-value for your tests and thereby conclude strong or weak support of the null hypothesis.

Probability values, or p-values, were popularized in the 1920s in statistics, though they’ve been around since the late-1700s. This value, which determines the «significance of results» in hypothesis testing, is used in various fields, from economics to criminology. In short order, it tells us the how strong a claim or null hypothesis is. Will the null hypothesis be proven out? Or will it be rejected in favor of the alternative hypothesis? The answer lies with the p-value(s).

P-Value Formula & Arguments

As said, when testing a hypothesis in statistics, the p-value can help determine support for or against a claim by quantifying the evidence.

The Excel formula we’ll be using to calculate the p-value is:

  • =tdist(x,deg_freedom,tails)

Where the arguments are:

  • x = t
  • deg_freedom = n-1 (degrees of freedom)
  • tails = 1 for a one-tail test or 2 for a two-tail test

Significance Level & Testing

A common significance level used is 0.05, which says that if the resultant p-value is equal to or less than 0.05, then there’s strong evidence against the null hypothesis (and enter the alternative hypothesis). If the p-value is greater, then the null hypothesis has merit.

And so to solve the p-value in an Excel spreadsheet, simply select a cell and type in =t-dist( to bring up the formula and then type in the arguments, separating each by a comma:

If we use 0.05 as the significance level, then from this set, what do we find? Cons >

Pretty cool. Ready to carry out some hypothesis testing of your own? As you fire up the Excel, check out the original tutorial below by YouTube user meaniefiene. While it’s seen using an older version of Excel, the function works the exact same way on newer versions, no matter if you’re using Excel on a Windows or Mac computer.

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Cover photo by Justin Meyers/WonderHowTo

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