Statistics Linear Regression

University:
Bradley University
Course:
MTH 325 | Probability and Statistics I
Academic year:

2022
Views:

451

Pages:

4
Author:

iwanankgfd

LINEAR REGRESSION CORRELATION COEFFICIENT The correlation coefficient is a statistical measure of the strength of the relationship between the relative movements of two variables. A calculated number greater than 1.0 or less than -1.0 means that there was an error in the correlation measurement. HOW TO CALCULATE Use the formula (zy)i = (yi – ȳ) / s y and calculate a standardized value for each yi. Add the products from the last step together. Divide the sum from the previous step by n – 1, where n is the total number of points in our set of paired data. The result of all of this is the correlation coefficient r. Example- LEAST SQUARES The least squares method is a statistical procedure to find the best fit for a set of data points by minimizing the sum of the offsets or residuals of points from the plotted curve. Least squares regression is used to predict the behavior of dependent variables. HOW TO FIND Steps 1. Step 1: For each (x,y) point calculate x2 and xy. 2. Step 2: Sum all x, y, x2 and xy, which gives us Σx, Σy, Σx2 and Σxy (Σ means "sum up") 3. Step 3: Calculate Slope m: 4. m = N Σ(xy) − Σx Σy N Σ(x2) − (Σx)2 5. Step 4: Calculate Intercept b: 6. b = Σy − m Σx N. 7. Step 5: Assemble the equation of a line. Example CHI SQUARES TEST Pearson's chi-square test is a test used to determine whether or not there is a statistically significant difference between expected frequencies and observed frequencies in one or more categories of a contingency table. WHERE IT CAN BE USED The Chi Square statistic is commonly used for testing relationships between categorical variables. The null hypothesis of the Chi-Square test is that no relationship exists on the categorical variables in the population; they are independent. Examples - Color Status Frequency Blue Dead 7 Blue Alive 129 Gold Dead 9 Gold Alive 46 Red Dead 24 Red Alive 215

Statistics Linear Regression

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