Let's solve for d.
fd=(7)(1.06)d
Step 1: Add -7.42d to both sides.
df+−7.42d=7.42d+−7.42d
df−7.42d=0
Step 2: Factor out variable d.
d(f−7.42)=0
Step 3: Divide both sides by f-7.42.
d(f−7.42)f−7.42=0f−7.42
d=0f−7.42
Answer:
d=0f−7.42
PLEASE MARK ME AS BRAINLIEST
(a) Data with the eight day's measurement.
Raw data: [60,58,64,64,68,50,57,82],
Sorted data: [50,57,58,60,64,64,68,82]
Sample size = 8 (even)
mean = 62.875
median = (60+64)/2 = 62
1st quartile = (57+58)/2 = 57.5
3rd quartile = (64+68)/2 = 66
IQR = 66 - 57.5 = 8.5
(b) Data without the eight day's measurement.
Raw data: [60,58,64,64,68,50,57]
Sorted data: [50,57,58,60,64,64,68]
Sample size = 7 (odd)
mean = 60.143
median = 60
1st quartile = 57
3rd quartile = 64
IQR = 64 -57 = 7
Answers:
1. The average is the same with or without the 8th day's data. FALSE
2. The median is the same with or without the 8th day's data. FALSE
3. The IQR decreases when the 8th day is included. FALSE
4. The IQR increases when the 8th day is included. TRUE
5. The median is higher when the 8th day is included. TRUE
Hey!
Your answer would be:
x-intercept: The number of cups of lemonade that must be sold to break even.
y-intercept: Money spent before the sale of the first cup of lemonade.
Took the test <3
Answer:
Step-by-step explanation:
Given is a paired data which consist of temperatures (X in mm) and growth
We have to find the linear correlation i.e. the measure of association between these two variables.
x y xy x^2 y^2
62 36 2232 3844 1296
76 39 2964 5776 1521
50 50 2500 2500 2500
51 13 663 2601 169
71 33 2343 5041 1089
46 33 1518 2116 1089
51 17 867 2601 289
44 6 264 1936 36
79 16 1264 6241 256
Mean 58.88888889 27 1623.888889 3628.444444 916.1111111
cov 33.88888889
std dev x 13.43916333 14.50861813
sx *sy
r 0.195529176
Hence we find that correlation coefficient 0.1955.
62 dollars i think tho i'm not very sure, sorry for not knowing exactly but god bless and have a good day/night/week/month/year/life <3
