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The population of interest is the entire student body of NOHS,
and the sample was a random drawing of 100 students. I used a
random number generator from Minitab. From the randomly choosen
students on the list, I went through each
students schedule and picked a class, lunch or study hall they
may be in to fill out the survery.
On the survery there were three questions:
1)Are you
male or female?
2) Are you in any student activites
(sports, clubs, academic teams...)
and how many are you in 0.. 1.. 2.. 3.. 4.. 5.. over 5
3) About how many absences have you had this whole
year?(Days or partial days missed count the same! Refer to
guidance or report cards). 0.1.2.3.4.5..over 5
β = The
increase in days absent for each new activity.
Ho: β= 0
Ha: β ≠ 0
α=.05
Assumptions: samples are random, The distributon of e at any
particular x value has mean value of 0 (µe=0),
The standard deviation of e is σ, which does not depend on x,
The distribution of e at any particular x value is normal, The
random deviations associated with diffrenct observations are
independent of one another.
Regression
Analysis: Days Absent versus Number of
Activities
The regression equation is
Days Absent = 3.944 + 0.0278 Number of Activities
Predictor
Coef SE Coef
T P
Constant
3.9437 0.2996
13.17 0.000
# of Activites 0.0278
0.1671 0.17
0.869
S = 1.47407 R-Sq = 0.1% R-Sq(adj) = 0.0%
Analysis of
Variance
Source
DF SS
MS F
P
Regression
1 0.060 0.060
0.03 0.869
Residual Error 40
86.916 2.173
Total
41 86.976
Unusual Observations
Number of
Days
Obs Activities
Absent Fit
SE Fit
Residual
St Resid
15 0.00
0.000
3.944
0.300
-3.944
-2.73R
21 5.00
5.000
4.083
0.680
0.917
0.70 X
27 1.00
1.000
3.972
0.229
-2.972
-2.04R
29 1.00
0.000
3.972
0.229
-3.972
-2.73R
32 2.00
1.000
3.999
0.267
-2.999
-2.07R
R
denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
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