Question 1 : Find ?¯x¯ and ?¯y¯. (Leave your answer exact as a simplified fraction.) Question 2: Find the fitted regression line ?̂ =?0+?1?y^=b0+b1x . (Leave all numbers exact as simplified fractions.) Question 3: Estimate the model error variance ?2σ2 from the data. (Leave exact as a simplified fraction.) Question 4: Find a 95% confidence interval for ?1β1. (Round to 2 decimal places.)
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.
y | 9 | 7 | 6 | 5 | 3 |
x | 0 | 1 | 2 | 3 | 4 |
Question 1 : Find ?¯x¯ and ?¯y¯. (Leave your answer exact as a simplified fraction.)
Question 2: Find the fitted regression line ?̂ =?0+?1?y^=b0+b1x . (Leave all numbers exact as simplified fractions.)
Question 3: Estimate the model error variance ?2σ2 from the data. (Leave exact as a simplified fraction.)
Question 4: Find a 95% confidence interval for ?1β1. (Round to 2 decimal places.)
Question 5: Find a 95% confidence interval for ?0β0. (Round to 2 decimal places.)
 alt="0.1
0.05
0.025
0.01
0.005
0.001
0.0005
V
3.078
1.886
1.638
1.533
6.314
12.076
31.821
63.657
318.310
636.620
31.598
12.924
8.610
6.869
2.920
4.303
6.965
9.925
22.326
2.353
2.132
3.182
2.776
10.213
7.173
4.541
5.841
4.604
3.747
1.476
2.015
2.571
3.365
4.032
5.893
1.943
1.895
1.860
2.447
3.143
2.998
1.440
3.707
5.208
5.959
4.785
4.501
7
1.415
1.397
1.383
2.365
2.306
3.499
5.408
5.041
8
2.896
3.355
9
1.833
2.262
2.821
3.250
4.297
4.781
10
1.372
1.812
2.228
2.764
3.169
4.144
4.587
2.718
4.025
3.930
3.852
3.787
11
1.363
1.796
2.201
3.106
4.437
2.681
2.650
2.179
4.318
12
13
1.356
1.350
1.782
3.055
3.012
1.771
2.160
4.221
14
1.345
1.761
2.145
2.624
2.977
4.140
15
1.341
1.753
2.131
2.602
2.947
3.733
4.073
2.583
2.567
2.552
3.686
3.646
16
4.015
1.337
1.333
1.746
1.740
2.120
2.110
2.921
17
2.898
3.965
18
1.330
1.734
2.101
2.878
3.610
3.922
19
1.328
1.729
2.093
2.539
2.861
3.579
3.883
20
1.325
1.725
2.086
2.528
2.845
3.552
3.850
21
1.323
1.721
2.080
2.518
2.831
3.527
3.819
22
1.321
1.717
2.074
2.508
2.819
3.505
3.792
1.714
1.711
23
1.319
2.069
2.500
2.807
3.485
3.767
24
25
1.318
2.064
2.492
2.797
3.467
3.745
1.316
1.708
2.060
2.485
2.787
3.450
3.725
26
1.315
1.706
2.056
2.479
2.779
3.435
3.707
1.314
2.052
2.473
3.421
3.408
27
1.703
2.771
3.690
1.313
1.311
28
1.701
2.048
2.467
2.763
3.674
29
1.699
2.045
2.462
2.756
3.396
3.659
30
1.310
1.697
2.042
2.457
2.750
3.385
3.646
40
1.303
1.684
2.021
2.423
2.704
3.307
3.551
2.000
1.980
1.296
2.390
2.660
2.617
2.576
60
1.671
3.232
3.460
120
1.289
1.658
2.358
3.160
3.373
1.282
1.645
1.960
2.326
3.090
3.291
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