![]() ![]() Where \( X\) and \( Y\) are the variables (or values ?of those variables) and \(a\) and \(b\) are constants or coefficients. The two-variable relation can be expressed as follows: To find out the relation between two variables, you must create a scatter diagram, where both variables are represented by their natural values. Nothing special needed for the creation of the scatter diagram, all you need is a list of pairs of values for each variable. What tool to use to make a scatter diagram? These trends are not easy to analyze and they change over time (for example, when stock prices fall for long periods of time, some investors may lose interest in stocks). When you predict the stock price in the future, you should take into account these trends, such as how many stocks will be sold by an increase or decrease in price. This situation is used to illustrate a trend. Also, sales decrease when the price of the product is decreased by more than $5 million. It sells more products by price increases than by quality increases (the sales increased by more than $5 million after each increase in quality). But to predict the future rise (we will use this set of data to test our model), we need to solve for past values for this variable.Įxample: The XYZ Company sells many different products. To measure this rise, we use a data point called the current value. To find out the price of a stock at present, you need to know how much it has risen in the past. The correlation between the two variables is +0.596, so it indicates a positive or high correlation between the variables in question. This means that we can use this influence to predict the future price of the stock. 069) for the variable income which is significantly different from zero.Įxample: If there are interests in a certain stock and the price of that stock rises, the number of people who buy that stock will also increase. ![]() Similarly, we get a negative correlation coefficient (r = -0. Height is independent of weight so we get a positive correlation Coefficient (r = +0.177). Scatter Diagram Why does it work for these data? – Relationship between variables in opposite directions for example, when height increases and weight decreases. for example, when height and weight increase together, or when debt and income increase together. – Relationship among variables in the same direction. It can be defined as the proportion of pairs in which both variables are in the same direction (positive numbers) or both are in opposite directions (negative numbers).Īlthough scatter diagrams are not drawn with every data set, there are a few data sets where scatter diagrams should be used. The correlation coefficient between two variables is also sometimes called an r-value. Where, \( X\) represents the independent variable (height or weight), and \( Y\) represents the dependent variable (height or weight). For example, from the scatter diagram we can find out that the height and weight of a person have some relation with each other. A Scatter diagram can be used to find out the correlation between the variables. ![]() What is the scatter Diagram and why it is used?Ī Scatter diagram is a pictorial presentation of the relation between two variables. ![]()
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