# correlation-analysis.pptx

1 de Jun de 2023
1 de 22

### correlation-analysis.pptx

• 2. CorrelationAnalysis is a process for establishing the relationships between two variables. The measure is best used in variables that demonstrate a linear relationship between each other..
• 3. CorrelationCoefficient ( R ) or the Pearson’s product moment correlation coefficient in honor of its developer Karl Pearson ). It is numerical measure of the linear relationship between two variables usually labeled x and y.
• 4. Scattergram is composed of the points plotted in the rectangular coordinate system, where x and y are respectively the values of the independent and dependent variables. It is useful when there are a large number of data sets. They provide the following information about the relationship between two variables: •Strength •Shape –linear, curved, etc. •Direction •Presence of outliers
• 12. Interpretationof “r”orcorrelation coefficients: Between ±0.80to ±0.99 High correlation Between ±0.60to ±0.79 Moderately high correlation Between ±0.40to ±0.59 Moderately correlation Between ±0.20to ±0.39 Low correlation Between ±0.01to±0.19 Negligible correlation
• 13. r
• 14. The correlation coefficient, r, has a specific range of values:
• 15. Note that: •r never lies outside this range, therefore r = 2 is a nonsense answer whose only explanation can be "I made an arithmetic error". •r =1 is perfect positive correlation and all the data points lie exactly on a straight line with positive gradient. •r = -1 likewise is perfect negative correlation. •r is often measured or referred to as a percentage. In this case, the range is from -100% to 100% (remembering that 100% is the same as 1)
• 16. Steps you need to follow: 1.draw the scatterplot; 2.draw the trend line which describes the direction of the data; 3.evaluate how closely the cloud of data points clusters around the line; 4.determine what r value and what word descriptor best suits the data cloud.
• 17. The following diagram has a number line of r values to help you assigning the numbers and the word descriptors.
• 18. x y x2 y2 Student Scores in Scores in Statistic s 1 English (x) 36 (y) 21 2 42 18 3 37 15 4 31 11 5 25 15 6 28 9 7 33 10 8 28 20 9 42 16 10 39 11 11 38 21 12 40 14 N =12 ∑x= ∑y= ∑xy= ∑x2= ∑y2=
• 20. Studen t Scores in Scores in Statistic s x y x2 y2 English (x) (y) 1 36 21 756 1296 441 2 42 18 756 1764 324 3 37 15 555 1369 225 4 31 11 341 961 121 5 25 15 375 625 225 6 28 9 252 784 81 7 33 10 330 1089 100 8 28 20 560 784 400 9 42 16 672 1764 256 10 39 11 429 1521 121 11 38 21 798 1444 441 12 40 14 560 1600 196 SUM: 419 181 6384 15001 2931