a. The acceleration of the car is zero
Ans. When the acceleration of car is zero it means car is moving with constant velocity.
b. The acceleration of the car is to the east
Ans. The acceleration of car is in opposite directions which means the car is
Probability Models for random phenomena
No mathematical model exists that
allows perfect prediction the
There exists a
that allows perfect
RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS
A quantitative variable that assumes an outcome
of a random event.
A numeric outcome that results from an
For each element of an experiments sample
space, the random
Types of Distribution
Normal (Gaussian) Distribution
Shape of Data
The measures of center describe the
L = 0.05 m
A = 1 10-6 m2
Young modulus = 2 109 N/m2
F = 20 N
l = ?
We know that young modulus is given by:
= (F/A) / ( l/l)
l = F/A.l.
= 20/1 10-6 0.502 109
l = 0.02 m
P = gh
For water = 1000 kg/m3
P = 1000 9.8 94 = 921200 Pa
(Note: 101325 Pa = 1
2. Global Effluent Requirements (ger)
The Global Effluent Requirements apply to industrial wastewater discharges from all factories that
finish or launder garments for Levi Strauss & Co. (LS&CO.). For information regarding domestic
Masood Textile Mills LTD
Waste Water Treatment Plant
Technical Specification of Waste Water Treatment plant:
It is a bio- chemical process.
Waste water treatment plants Capacity.
Maximum Dyeing Fabric production.
(60% Dyed Fabric
40% White wash fabric)
a. Let G = fine egg, P(G) = 5/8 = 0.675
Let F = spoiled egg, P(F) = 3/8 = 0.325
Possible outcomes for two eggs selected randomly without replacement = cfw_GG, GF, FF, FG
b. Probability of GG = 5/8 4/7 = 0.3571
Probability of GF = 5/8 3/7 = 0.2679
Q1 Let (x,y,z) the three positions and x represents my position
Part a) List all the possible outcomes in S
Solution: In this case we use formula of permutations with replacement as follows.
or PR(n,r) = nr If we choose r elements from a set size of n, ea
Exploring the relationships between two or more variables.
Simple Linear Regression - Single regressor or predictor, x and a
dependent or response variable Y.
Multiple Linear regression - More than one predictor