KEY FORMULAS Jaggia and Kelly Essentials of Business Statistics Communicating with Numbers
g
Chapter 7: Sampling and Sampling Distributions
Topic
Formula
Expected Value of the Sample Mean
E X
Standard Error of the Sample Mean
se X
Standard Transformatio
Chapter 8 Interval Estimation:
2. (case 2) If 1 and 2 are unknown but assumed
equal then we use the pooled t test statistic: 1)
=pooled variance
Confidence Intervals:
90%, a = 0.10, a/2 = 0.05, za/2 = z.05 =
1.645.
95%, a = 0.05, a/2 = 0.025, za/2 = z.025
Chapter 1:
Mean: add up all #/ x amount of #
Median: middle number (1,2,3,4,5)
Standard Deviation: Use calculator function 2nd Data,
then 2nd STAT and go to Sx=
Range = Max Min
Mode: is double
Chapter 2:
Frequency Distribution table:
Conditional Probabili
Chapter 1:
Mean: add up all #/ x amount of #
Median: middle number (1,2,3,4,5)
Standard Deviation: Use calculator function 2 Data, then 2
STAT and go to Sx=
Range = Max Min
Mode: is double
Chapter 2:
Frequency Distribution table:
nd
Chapter 4: Introductio
KEY FORMULAS Jaggia and Kelly Essentials of Business Statistics Communicating with Numbers
g
Chapter 3: Numerical Descriptive Measures
Topic
Formula
Sample Mean
x
Population Mean
xi
N
Weighted Mean
x wi xi
Percentile Location
L p n 1
Range
Range = Max M
47. More and more households are struggling to pay utility bills given a shaky economy and high heating costs
(The Wat.r Street Journal, February 14, 2008). Particularly hard hit are households with homes heated with
propane or heating oil. Many of these
Chapter 4 - LO 4.1 4.2 4.3 4.4 4.5 4.6 4.7
LO 4.1
Describe fundamental probability concepts.
Probability - is a numerical value that measures the
likelihood that an event occurs.
The value of a probability is between zero (0) and
one (1).
A probability
#5.
Let B = bus C=car T = train
L = late
(a) Given in the problem:
P(B) = P(C) = P(T) = 1/3 = .3333
P(L|B) = 0.2
PL|C) = 0.5
P(L|T) = 0.01
Want P(C|L) = _P(C) x P(L|C)_
P(C) x P(L|C) + P(B) x P(L|B) + P(T) x P(L|T)
= _(.3333 x 0.5)_
(.3333x.05) +(.3333x0.
47. More and more households are struggling to pay utility bills given a shaky economy and high heating costs
(The Wall Street Journal, February 14, 2008). Particularly hard hit are households with homes heated with
propane or heating oil. Many of these h
Chapter 4 Probability Problems
1. Where people turn to for news is different for various age groups. Suppose that a study was
conducted of 400 respondents of which 200 were between the ages of 35 and 50 and 200 were
over the age of 50. The table below sum
Chapter 4 Class Handout
A manufacturer is interested in whether there is any relationship between age and potential to
purchase a certain product. A survey of 500 individuals provided the following results:
Age
Young
Middle
Old
Total
(Y)
(MA)
(O)
Potentia
Calculator Instructions
To set the number of decimals: Press the following keys
(this makes the number of decimal places floating)
[2ND] [.] [ENTER] [9] [ENTER] [CE/C] [CE/C]
To calculate the mean, variance and standard deviation (Univariate Data)
The fol
Chapter 4 Bayes Example
An auto insurance separates its clients into 3 age groups: Group A includes those under 25 years old,
Group B includes those 25-39 years old, and Group C includes those 40 years old and older. Group A
represents 25% of total policy
A manufacturer is interested in whether there is any relationship between age and potential to
purchase a certain product. A survey of 500 individuals provided the following results:
Age
Young
Middle
(MA)
Old
Total
(Y)
(O)
Potential to Purchase
High
Mediu
Choir/W L/ 5.2ng Erma/e
An auto insurance separates its clients into 3 age groups: Group A includes those under 25 years old,
Group B includes those 25-39 years old, and Group C includes those 40 years old and older. Group A
represents 25% of total policy
Chapter8
ConfidenceIntervals
Calculatingwithpopulationmean,
known:ztable
Width=
2 z 2
n
Marginoferror:E= z
x
z
( n )
( n )
< < + z
x
( n )
=(1 ( confidence level)
twotail:
=(1 )
2
Confidencelevel:%
ConfidenceCoefficient:Decimal
unknown: ttable
S
1. There is an inverse relationship between Speed and Noise. This evidenced by looking
at the raw data and confirmed by the graphical representation.
2. The noise is much more variant than distance, which has a nearly constant slope.
3. At 400 distance, t