Complete Question:
Attached below as picture.
Answer:
From first graph there is no linear pattern so here linearity assumption violated.
From second graph there is observation is in some pattern like funnel or v shape so there is no constant variance occur that is there is no constant variance for error.
Constant variance for error occur when in residual plot all observation are in scatter everywhere.
From third graph we can say there is positive distribution but for regression analysis we need symmetric that is normal distribution.
Step-by-step explanation:
See graphs attached below.
Answer:
Step-by-step explanation:
A box plot is the diagrammatic representation of the five number summary. It includes 5 items:
The minimum.
Q1 = the first quartile or the 25% mark.
The median.
Q3 = the third quartile or the 75% mark.
The maximum.
Rearranging the data in ascending order, it becomes
169, 163, 153, 166, 149, 148, 146, 145, 152, 163
145, 146, 148, 149, 152, 153, 163, 163, 166, 169
Minimum = 145
Maximum = 169
Median = (152 + 153)/2 = 152.5
The median divides the data into two equal halves. The middle of the lower halve is Q1 while the middle of the upper halve is Q3
Q1 = 148
Q3 = 163
The diagram of the box plot is shown in the attached photo
N - 5 ≥ -2
5 - 5 ≥ -2
5 - 5 = 0
n = 5
5 - 5 ≥ -2
5 - 5 = 0
(0 ≥ -2)
If I could get more context then that would help. Because an exponent being an odd number doesn’t do anything, so it could be either a negative or a positive
Answer:
−6.7 + (−2 1/ 5 )
Step-by-step explanation:
−6.7 + (−2 1/ 5 )
