NormalDistributions
The normal distribution has two parameters: the mean () and the standard
deviation (). Each different combination of and specifies a different normal
distribution. The normal distribution is symmetrical about its mean and is bellshaped
Simple Linear Regression
Simple linear regression is used to analyze the nature of the relationship between two variables.
The dependent (response) variable is designated by Y and the independent (explanatory) variable
is designated by X. For a given inde
Inference for 2 Populations
Comparison of 2 Population Means (Independent Samples):
H0: 1 - 2 = 0 (1 = 2).
H1: 1 - 2 0 (1 2).
TS:
( x1 x 2) (1 2)
( x1 x 2)
.
AL: z(1 - /2).
Note: Use +z(1 - ) for UTTs and use -z(1 - ) for LTTs.
What value should be used f
Hypothesis Testing: One Population
Hypothesis testing is used to make decisions about a population based on the analysis of sample
statistics. There are always two hypothesis statements which are mutually exclusive and
complementary statements concerning
Inference for Two-Way Tables
Contingency Table Test for Independence:
H0: The two criteria are independent of each other.
H1: The two criteria are not independent of each other.
*OR*
H0: p1 = p2 = p3 = = pi (The populations are homogeneous).
H1: Not all p
OverviewofInference
Methods for drawing conclusions about a population
from sample data are called statistical inference.
Methods:
Confidence Intervals - estimating a value of a
population parameter.
Hypothesis Tests - assessing evidence for a claim
abo
SmallSampleSizes
The sample standard deviation s provides an estimate of the
population standard deviation .
When the sample size is large,
it is likely to contain elements
representative of the whole
population. Then s is a good
estimate of .
But when th
One-Way Analysis of Variance (ANOVA)
ANOVA tests for the equality of two or more population (treatment) means.
Assumptions:
1.
All populations are normally distributed.
2.
All populations have the same variance: 12 = 22 = 32 = . = r2 = 2.
3.
Independent r
Business Statistics
Final Project
Guillaume Lostie de Kerhor 260505805
Nicolas Schwab 260503993
Alexis Randolph 260521329
Amaury Vangrevelynghe 260508021
Introduction
In this report, a set of data about Student's involvement in Sports at University is ana
TowardStatisticalInference
Inferential statistics involves using a representative subset of data (a sample)
in order to draw conclusions about unknown characteristics of an entire set of
elements (a population). The estimate of the population parameter is
Scatterplot
A graph showing the shape and direction of the underlying relationship between two
variables.
Observations are plotted in pairs with one variable plotted on each axis.
Typically, the explanatory or independent variable is plotted on the X axis
WelcometoBusinessStatistics!
Statistics is the science of getting insight from data in context.
Knowing how to carry out calculations or construct graphs little
value.
Knowing which calculations and graphs are appropriate
worthwhile.
Knowing what those c
RandomnessandProbability
A phenomenon is random if individual
outcomes are uncertain, and there is a
distribution of outcomes in a large
number of repetitions.
The probability of any outcome of a random phenomenon can be
defined as the proportion of times
ObtainingData
Available data were produced in the past for some other purpose but that
may help answer a present question inexpensively. The library and the
Internet are sources of available data.
Government statistical offices are the primary source for
RandomVariables
A random variables numerical value is determined by the outcome of a
random phenomenon.
i.e. A basketball player shoots three times. We can define a random
variable X as the number of baskets successfully made.
A discrete random variable c
DescriptiveStatistics
Descriptive statistics involves organizing, summarizing and
illustrating statistical data. The objective is to show important
characteristics of the data without drawing any conclusions.
Measures of position: mean, median, mode
Refer