I need perfect solution step by step if i dont got perfect score my teacher will marked me failed and i will repeat this school year please help me this is the last chance given to me:

Activity 1: Determine the direction of relationship between the following pairs of variables. Is it positive, 8 21 negative or zero? 1. weight and height of students 2. weight and age of students 3. age and height of trees 4. number of customers and sales in a department store 5. pressure and volume of gas 6. IQ and height of person 7. amount of rainfall and amount of agricultural harvest 8. area and length of a side of square 9. speed and mileage of a car 10. Extent of fatigue and performance in a speed test. Day 2: Activity 2: The following data show the attitude score and mathematics achievement of a group of students. a. Construct a scatter plot for the given data. b. Describe the relationship between attitude and achievement in Mathematics in terms of direction and strength based on the scatter plot Attitude Score (X) Achievement in Mathematics (Y) 48 22 48 19 47 20 46 20 46 17 43 21 42 21 42 19 41 17Activity 3: The following data were obtained from a group of students regarding the number of hours that they devoted for studying and the grades that they obtained in their examination. a. ' Construct a seatter plot for the given data. b. Describe the relationship between the number of hours spent on study and the examination grades in terms of directionjand'strength based on the scatter plot. CONTENT DISCUSSION: (For Self-Paced Learning) If you have queries or questions regarding the content provided, please feel free to consult or message the subject teacher through messenger, text, call, or video chat) Understanding Correlation Analysis Gear Up: Why do most students who are good in Mathematics also perform well in physics? Why does blood pressure go with age? Why do students with high IQ have good academics performances? These questions have something to do with relationships between two variables. Analyze and Explore So far we have analyzed data involving only a single variable---for instance, the grades of students, the weights of grocery products and the length of rods. These data are called UNIVARIATE DATA because they involve a single variable only. In this lesson you shall analyze data involving two variables. Data that involve two variables are called BIVARIATE DATA. The analysis of bivariate data involves describing the relationship between two variables. The process or procedure of describing the relationship between two variables is called CORRELATION ANALYSIS. DESCRIBING RELATIONSHIP USING A SCATTER PLOT The relationship between two variables can be described by constructing a scatter plot. A scatter plot is a graphical representation of the relationship between two variables. Example: A company with six branches provides free coffee to its employees. A manager is interested to find out if there is a relationship between the number of cups of coffee provided and the number of employees in the offices. The table below shows that data needed. Determine if there is a relationship between the number of employees and the number of cups of coffee. Number of Employees (X) Number of Cups (Y) 11 18 13 36 15 40 18 50 21 58 74 Number of Cups of Coffee 10 20 30 40 50 60 70 80 90 X Number of Employees Notice that the points on the scatter plot do not lie on the one line. How ever, the points closely follow a straight line. This line is called TREND LINE. The relationship between two variables is described in terms of strength and direction. TYPES OF CORRELATION ACCORDING TO DIRECTION In terms of direction, the relationship between two variables may be positive, negative or zero.Positive Correlation A positive correlation exists if high values in one variable are associated with high values in another variable. Similarly, low values in one variable are associated with low values in the other variable. If a positive correlation exists, then the points on the scatter plot closely follow a straight line slanting up to the right. Negative Correlation A negative correlation exists if high values in one variable are associated with low values in another variable. Similarly. low values in one variable are associated with high values in the other variable. If a negative correlation exists, then the points on the scatter plot closely follow a straight line slanting down to the right Zero Correlation A zero correlation exists when high values in one variable are associated to either high or low values in the other variable. If a zero correlation exists, then the points on the scatter plot are randomly scattered. The points do not follow closely a straight line. Types of Correlation according to Strength A perfect correlation exists when all the points on the scatter plot lie on a straight line. When the points on the scatter plot do not lie on a straight line, the relationship may be very high, high, moderately high, low, negligible, or zero. The next illutration show the different types of relationship described in terms of direction and strength. 23 Perfect Positive Correlation Perfect Negative Correlation High Positive Correlation High Negative CorrelationA zero correlation exists when high values in one variable are associated to either high or low values in the other variable. If a zero correlation exists, then the points on the scatter plot are randomly scattered. The points do not follow closely a straight line. Types of Correlation according to Strength A perfect correlation exists when all the points on the scatter plot lie on a straight line. When the points on the scatter plot do not lie on a straight line, the relationship may be very high, high, moderately high, low, negligible, or zero. The next illutration show the different types of relationship described in terms of direction and strength. 23 Perfect Positive Correlation Perfect Negative Correlation X High Positive Correlation High Negative Correlation Low Positive Correlation Low Negative Correlation