Statistics for Literary Studies 2025

• These notes are about statistics for third-year secondary students in literary studies for 2025

Contents of the memorandum

• Comprehensive explanations for each lesson
• Homework for each lesson
• In-class exercises
• Question bank for each unit

Terms of Use

• It is forbidden to put another person's name on the series due to possible religious concerns; however, it can be used without a name if there is a reason
• The author's name is written only on the first page without any watermarks
• It is forbidden to replace the series' name (Al-Siraj) with any other name
• Send the author notes regarding the format or content for modification
• The series should not be exchanged with another teacher as a gift or sale without the publisher's knowledge

Forthcoming Edition

• A series of cumulative tests for the first preparatory grade
• Each test includes the lesson and its previous lessons

Communication

• Khaled Saad Mathematics Group on Facebook
• WhatsApp: 01027064155 - Phone: 01093451116

Correlation and Regression - The First Unit

• Correlation

Correlation Defined

• A statistical method to determine the degree and type of relationship between two variables

Note

• There is a direct correlation between a person's height and weight, so increasing the height leads to an increase in weight and vice versa
• There is an inverse correlation between altitude above sea level and temperature; as altitude increases, temperature decreases

Scatter Plot

• A graphical representation of a number of ordered pairs (x, y) to describe the relationship between two variables
  • There is no correlation
  • There is a linear inverse correlation
  • There is a linear forward correlation

Linear Correlation

• The simple linear correlation is a measure of the degree of the relationship between the variables

Correlation Coefficient

• The correlation coefficient r is a relative quantitative measure that measures the strength of the correlation between two variables

Notes

• The correlation coefficient r ranges between -1 and 1
  • r = 1 indicates a complete positive correlation
  • r = -1 indicates a complete negative correlation
  • r = 0 indicates no correlation
• The closer the absolute value of the correlation coefficient is to 1, the stronger the correlation
• If r > 0, there is a positive correlation
  • The closer the value of the correlation coefficient is to 1, the stronger the forward correlation
• If r < 0, there is a negative correlation
  • The closer the value of the correlation coefficient is to -1, the stronger the forward correlation
• If the correlation between x and y is positive, then r can equal 0.6

Pearson's Correlation Coefficient

• n is the number of pairs
• Ex is the sum of x values
• Ey is the sum of y values
• Exy is the sum of the product of x and y values for each pair

Solve the following

• Calculate Pearson's correlation coefficient between x and y

Calculate Pearson's correlation coefficient between x and y

Solve the following

• Calculate Pearson's correlation coefficient between x and y

Training

• If from the following table find Pearson's linear correlation coefficient and determine its type

Spearman's Rank Correlation Coefficient r

• Can be used in quantitative and descriptive data

From the following table, calculate the rank correlation coefficient for Spearman between x, y

- If values of x are arranged in descending order, the same value for the correlation coefficient r is obtained

Training

• From the following data, calculate Spearman's rank correlation coefficient
• From the following table, calculate Spearman's rank correlation coefficient