Assuming these are sample data, answer the following questions. You may use statistical software to assist you. a. What is the correlation coefficient between these variables? interpret your results. b. At the .05 significance level, can you conclude there is a negative association between “points scored' and “points allowed’? Wins Points Scored Points Allowed 4 333 441 7 359 392 6 329 349 5 245 316 8 360 341 4 290 467 6 368 455 7 281 359 13 527 384 5 396 464 7 319 433 9 428 360 6 376 400 11 436 325 5 369 412 3 225 425 12 421 283 9 367 348 9 310 303 12 565 421 10 389 287 11 402 316 6 269 374 13 504 353 6 324 360 10 428 347 10 433 344 4 342 435 10 339 324 7 376 382 12 428 329 7 414 423
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Assuming these are sample data, answer the following questions. You may use statistical software to assist you.
a. What is the
b. At the .05 significance level, can you conclude there is a negative association between “points scored' and “points allowed’?
| Wins | Points Scored | Points Allowed |
| 4 | 333 | 441 |
| 7 | 359 | 392 |
| 6 | 329 | 349 |
| 5 | 245 | 316 |
| 8 | 360 | 341 |
| 4 | 290 | 467 |
| 6 | 368 | 455 |
| 7 | 281 | 359 |
| 13 | 527 | 384 |
| 5 | 396 | 464 |
| 7 | 319 | 433 |
| 9 | 428 | 360 |
| 6 | 376 | 400 |
| 11 | 436 | 325 |
| 5 | 369 | 412 |
| 3 | 225 | 425 |
| 12 | 421 | 283 |
| 9 | 367 | 348 |
| 9 | 310 | 303 |
| 12 | 565 | 421 |
| 10 | 389 | 287 |
| 11 | 402 | 316 |
| 6 | 269 | 374 |
| 13 | 504 | 353 |
| 6 | 324 | 360 |
| 10 | 428 | 347 |
| 10 | 433 | 344 |
| 4 | 342 | 435 |
| 10 | 339 | 324 |
| 7 | 376 | 382 |
| 12 | 428 | 329 |
| 7 | 414 | 423 |
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