⚠ Switch to EXCALIDRAW VIEW in the MORE OPTIONS menu of this document. ⚠
Text Elements
Experiment - seats were treatments
So that people dont clique up into groups of their friends with similar academic opinions - allows us to conclude cause and effect.
2 variables quanitative
x is row y is score
-1.51, you lose an average of 1.51 points for each row back you move
85.95-1.51x
y
=
1 sample t test for slope
β = true slope of population LSRL
H0: b = 0 Ha: b < 0
0.05
0.132
-1.14
.132 > .05
fail to reject
do not have
there is a
negative linear relationship between seat location and test score
t(28)
df=28 (n-2)
.132
sample stat
population parameter
phat
proportions
p
mean
xbar
mue
slope
b
Beta
yint
a
alpha
SD/SE of slope
ohat
SE
b
b
Significance Tests:
Choose:
1 sample t test for slope
H0: B=0
Ha: B != < > 0
Check:
Calculate: stat → edit → data in l1 & l2
→ test → linregttest
- df = n - 2
a = 2.8871 for people that are 0 years old ( newborns ) , we predict their ear height to be 2.8871 on average
b = 0.0021 for each increase of 1 year in age, we predict the ear height to increase by 0.0021 cm
SEb = 0.0059 the slope of the sample LSRL typically varies from the slope of the population LSRL by about 0.0059 cm/year b varies from B by ~.0059
Embedded files
54564aa8df8f2e448bde2ff5b74731a0680acd79: Pasted Image 20240408125344_023.png 98924ea53689f1a145da79ccdc49ad731c54fb99: Pasted Image 20240408134624_050.png
