If you are looking for ways to calculate **P-value** or probability value in** linear regression in Excel,** then you are in the right place. **P-value **is used to determine the probability of the results of hypothetical tests. We can analyze the results based on 2 hypotheses; the **Null hypothesis **and the **Alternative hypothesis**. Using the **P-value** we can determine whether the result supports the Null hypothesis or Alternative hypothesis.

So, letâ€™s get started with the main article.

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## 3 Ways to Calculate P Value in Linear Regression in Excel

Here, we have some predicted sales values and actual sales values of some of the products of a company. We will compare these sales values and determine the probability value and then we will determine if **P** supports the null hypothesis or the alternative hypothesis. The null hypothesis reckons there is no difference between the two types of sales values and the alternative hypothesis will consider differences between these two sets of values.

We have used *Microsoft Office 365* version here, you can use any other versions according to your convenience.

__Method-1__: Using â€˜t-Test Analysis Toolâ€™ to Calculate P Value

Here, we will use the analysis toolpak containing the t-Test analysis tool to determine the **P-value **for these two sets of sales data.

** Steps**:

If you didnâ€™t activate the data analysis tool then first enable this toolpak at first.

âž¤ Click on the

**File**tab.

âž¤ Select **Options**.

After that, the **Excel Options **dialog box will appear.

âž¤ Select the **Add-ins **option on the left panel.

âž¤ Choose the **Excel** **Add-ins **option in the **Manage **box and then press **Go**.

Afterward, the **Add-ins **dialog box will pop up.

âž¤ Check the **Analysis ToolPak **option and press **OK**.

âž¤ Now, go to the **Data **Tab >> **Analysis **Group >> **Data Analysis **Option.

Then, the **Data Analysis** wizard will appear.

âž¤ Select the option **t-Test: Paired Two Sample for Means **from different options of *Analysis Tools*.

After that, the **t-Test: Paired Two Sample for Means **dialog box will open up.

âž¤ As **Input **we have to provide two variable ranges; **$C$4:$C$11 **for **Variable 1 Range **and **$D$4:$D$11 **for **Variable 2 Range**, as **Output Range **we have selected **$E$4**.

âž¤ You can change the value for ** Alpha **from

**0.05**(automatically generated) to

**0.01**because the designated value for this constant is generally

**0.05**or

**0.01**.

âž¤ Finally, press

**OK**.

After that, you will get the **P-value** for two cases; the one-tail value is ** 0.00059568** and the two-tail value is

**. We can see the one-tail**

*0.0011913***P-value**is half times the two-tail

**P-value**. Because the two-tail

**P-value**considers both the increase and decrease of the marks whereas the one-tail

**P-value**considers only one of these cases.

*Moreover, we can see that for the Alpha value of*

**0.05**we are getting the**P**values less than**0.05**which means it neglects the null hypothesis and so the data is highly significant.**Read More:** **How to Interpret Linear Regression Results in Excel (with Easy Steps)**

__Method-2__: Using T.TEST Function to Calculate P Value in Linear Regression in Excel

In this section, we will be using the **T.TEST function** to determine the **P values** for tails ** 1 **and

**.**

*2*** Steps**:

We will start with determining the

**P-value**for tail

**or in one direction.**

*1*âž¤ Type the following formula in cell

**F5**.

**=T.TEST(C4:C11,D4:D11,1,1)**

Here, **C4:C11 **is the range of ** Predicted Sales**,

**D4:D11**is the range of

**,**

*Actual Sales***1**is the tail value and the last

**1**is for the

**type.**

*Paired*After pressing **ENTER**, we are getting the **P-value 0.00059568 **for tail

**.**

*1*âž¤ Apply the following formula in cell **F6 **to determine the **P-value **for tail *2 *or in both directions.

`=T.TEST(C4:C11,D4:D11,2,1)`

Here, **C4:C11 **is the range of ** Predicted Sales**,

**D4:D11**is the range of

**,**

*Actual Sales***2**is the tail value and the last

**1**is for the

**type.**

*Paired***Read More:**** Multiple Linear Regression on Excel Data Sets (2 Methods)**

__Method-3__: Using CORREL, T.DIST.2T Functions to Calculate P Value in Linear Regression

We will determine **P-value **for correlation here by using the **CORREL**, **T.DIST.2T** functions.

To do this we created some columns with headers ** Total Item**,

**,**

*Correl. Factor***, and**

*t Value***P value**and we entered the value for total items also which is

**8**.

** Steps**:

âž¤ Firstly, We determine the

**Correl.Factor**by entering the following formula in cell

**C14**.

`=CORREL(C4:C11,D4:D11)`

Here, **C4:C11 **is the range of ** Predicted Sales**, and

**D4:D11**is the range of

**.**

*Actual Sales*âž¤ To determine the **t value **type the following formula in cell **D14**.

`=(C14*SQRT(B14-2))/SQRT(1-C14*C14)`

Here, **C14 **is the correlation factor, and **B14 **is the total number of products.

**SQRT(B14-2)**becomes**SQRT(8-2) â†’ SQRT(6)Â**gives the square root of**6**.**Output â†’**2.4494897

**C14*SQRT(B14-2)**becomes**0.452421561*2.4494897****Output â†’**1.10820197

**1-C14*C14**becomes**1-0.452421561*0.452421561****Output â†’**0.79531473

**SQRT(1-C14*C14)**becomes**SQRT(0.79531473) â†’**returns the square root of**0.79531473**.**Output â†’**0.891804199**(C14*SQRT(B14-2))/SQRT(1-C14*C14)**becomes**(1.10820197)/0.891804199****Output â†’**1.242651665

âž¤ Finally, by using the following function we will determine the **P-value **for correlation.

`=T.DIST.2T(D14,B14-2)`

Here, **D14 **is the ** t value**,

**B14-2**or

**8-2**or

**6**is the degree of freedom and

**T.DIST.2T**will return the

**P-value**for correlation with the two-tailed distribution.

**Read More:** **How to Do Multiple Regression Analysis in Excel (with Easy Steps)**

## Things to Remember

â¦¿ Generally, we use two common ** Alpha **values;

**0.05**and

**0.01**.

â¦¿ There are two hypotheses, the null hypothesis, and the alternative hypothesis, the null hypothesis considers no difference between two sets of data and the other one takes into account the difference between two sets of data.

â¦¿ When the

**P-value**is less than

**0.05**it denies the null hypothesis and for values greater than

**0.05**it supports the null hypothesis. By assessing the

**P-value**we can come up with the following conclusions.

**P<0.05 â†’**highly significant data

**P=0.05 â†’**significant data

**P=0.05-0.1 â†’**marginally significant data

**P>0.1 â†’**insignificant data

## Practice Section

For doing practice by yourself we have provided a** Practice** section like below in a sheet named **Practice**. Please do it by yourself.

## Conclusion

In this article, we tried to cover the ways to calculate **P-value **in **linear regression in Excel.** Hope you will find it useful. If you have any suggestions or questions, feel free to share them in the comment section.

Hi, you present 3 methods to calculate p-values for the same data set. Supposedly, results should be independent of the method chosen. So an explanation for the difference obtained in one of the methods is needed. Thanks.

Hi Jose A. Valiente, thanks for your valuable suggestion. Actually, the third method is quite different from the first 2 methods as this method determines the P value for the correlation of the two sets of values using a correlation factor.