>Hello Sohib EditorOnline, in this journal article, we will be discussing how to calculate the R Table. For those of you who are not familiar with R Table, it is a statistical table used to determine the critical value of the Pearson correlation coefficient. Pearson correlation coefficient measures the strength and direction of a linear relationship between two variables.

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## What is R Table?

The R Table, also known as the Pearson Correlation Coefficient Table, is used to determine the critical value of the Pearson correlation coefficient. This table is used in hypothesis testing, where we test if there is a statistically significant correlation between two variables. The R Table is used to find the critical value for the test statistic, which is then compared to the calculated test statistic to determine if the null hypothesis should be rejected or not.

The R Table is a statistical table that provides the critical values for different levels of significance and degrees of freedom. The degrees of freedom depend on the sample size and are calculated by subtracting 2 from the number of observations.

### Table 1: R Table Values for Different Levels of Significance

Degrees of Freedom | 0.10 | 0.05 | 0.01 |
---|---|---|---|

1 | 0.994 | 0.997 | 0.999 |

2 | 0.899 | 0.950 | 0.990 |

3 | 0.828 | 0.878 | 0.959 |

4 | 0.777 | 0.811 | 0.917 |

Table 1 above shows the R Table values for different levels of significance at different degrees of freedom. To find the critical value for a specific degree of freedom and level of significance, we look up the corresponding value in the table.

## How to Use R Table?

To use the R Table, we first need to calculate the Pearson correlation coefficient, which is denoted by the symbol r. The formula to calculate r is:

r = ∑(X – X̄)(Y – Ȳ) / sqrt(∑(X – X̄)^2 ∑(Y – Ȳ)^2)

where X and Y are the two variables being correlated, X̄ and Ȳ are the means of X and Y, and ∑ represents the summation of the values.

Once we have calculated r, we need to determine the degrees of freedom, which is the number of observations minus 2. We then look up the value of r in the R Table for the corresponding degrees of freedom and level of significance. If the calculated value of r is greater than the critical value from the table, we can reject the null hypothesis that there is no correlation between the two variables. If the calculated value of r is less than or equal to the critical value from the table, we fail to reject the null hypothesis.

### FAQ

#### 1. What is Pearson correlation coefficient?

Pearson correlation coefficient measures the strength and direction of a linear relationship between two variables. It ranges from -1 to 1, where -1 indicates a perfect negative correlation, 0 indicates no correlation, and 1 indicates a perfect positive correlation.

#### 2. Why do we need to use R Table?

We use R Table to determine the critical value of the Pearson correlation coefficient. This is important in hypothesis testing, where we test if there is a statistically significant correlation between two variables.

#### 3. How do we know if the calculated value of r is statistically significant?

If the calculated value of r is greater than the critical value from the R Table, we can reject the null hypothesis that there is no correlation between the two variables.

#### 4. Can we use R Table for non-linear relationships?

No, R Table is only applicable for linear relationships between two variables. For non-linear relationships, we need to use other statistical tests.

## Conclusion

In conclusion, the R Table is a useful tool in hypothesis testing, where we test if there is a statistically significant correlation between two variables. By using the R Table, we can determine the critical value of the Pearson correlation coefficient and make an informed decision on whether to reject or fail to reject the null hypothesis. Understanding how to calculate and use the R Table is an important skill for anyone involved in statistical analysis.