Descriptive statistics
Describing data with numbers:
measures of location
What to describe?
What is the location or center of the data? (measures of location)
How do the data vary? (measures of variability)
Measures of Location
Mean
Median
Mode
The sisters must be familiar with an organizational structure which has two categories and
theyre formal and informal policies and procedures companies use for governing business
operations. Smaller and home based businesses typically do not use organizat
3.
The first step in the decision-making process is to identify and define the problem. Based
on what knowledge we have the main issue for the Fields farm is the fact that they do not have
the money to operate the farm as it has been operated. The expense
In a recent poll of 1000 adults, 55% of the respondents said that the use of marijuana should
not be made legal. In the same poll, 20% of the respondents said that the use of marijuana
for medical purposes should not be legal. (Answer both questions to ge
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Is time for a change? One of the issues we must address is the aging idea of an employee
engagement survey. While such measures of engagement have been used for years, organizations
tell us they arent providing modern, actionable solutions. Consider the t
Top managers use a number of methods to control their organizations. These executives
often start with corporate mission statements to communicate the company's primary objectives
to employees. Some objectives may include finding new markets for products,
Theyre many employee benefits such as retirement plans, health life insurance, life
insurance, disability insurance, vacation, employee stock ownership plans. Some employer
thinks benefits are increasingly expensive to them, so the range and options of be
Range
o Measure of variation
Difference between the largest and the smallest observations:
Ignores the way in which data are distributed
Interquartile Range
Measure of variation
Also known as midspread
Spread in the middle 50%
Difference between t
Ch. 8: Confidence Interval Estimation
o In chapter 6, we had information about the population and, using the theory of
Sampling Distribution (chapter 7), we learned about the properties of samples.
(what are they?)
o Sampling Distribution also give us th
Hypothesis Testing
o Goal: Make statement(s) regarding unknown population parameter values based
on sample data
Elements of a hypothesis test:
Null hypothesis - Statement regarding the value(s) of unknown
parameter(s). Typically will imply no associati
Important statistical terms
o Population:
a set which includes all
measurements of interest
to the researcher
(The collection of all responses, measurements, counts that are of
interest)
Sample:
A subset of the population
o Why sampling?
Get infor
Qualitative vs. Quantitative research methods:
o Qualitative research takes place in the real world, as opposed to the laboratory,
and deals with how people give meaning to their own experience.
o Then it is followed by an attempt to interpret the behavi
Data Types
o Introduction
- A data type defines a collection of data objects and a set of predefined
operations on those objects
- A descriptor is the collection of the attributes of a variable
- An object represents an instance of a user-defined (abstra
Test of significance
The test which is done for testing the research hypothesis against the null
hypothesis.
. Why it is done?
. To assist administrations and clinicians in making decision.
The difference is real ?
It is happen by chance ?
Due to stu
Multiple Regression Analysis (MRA)
o Method for studying the relationship between a dependent variable and two or
more independent variables.
Purposes:
Prediction
Explanation
Theory building
o Design Requirements
One dependent variable (criterion)
Chapter 2 Simple Linear Regression
o 2.1 Simple Linear Regression Model
y = b0 + b1 x + e
x: regressor variable
y: response variable
b0: the intercept, unknown
b1: the slope, unknown
e: error with E(e) = 0 and Var(e) = s2 (unknown)
The errors are
Review of observational study design and basic statistics for contingency tables
o According to scientists, too much coffee may cause.
1986 -phobias, -panic attacks
1990 -heart attacks, -stress, -osteoporosis
1991 -underweight babies, -hypertension
1
Correlation
o Sir Francis Galton (Uncle to Darwin
Development of behavioral statistics
Father of Eugenics
Science of fingerprints as unique
Retrospective IQ of 200
Drove himself mad just to prove you could do it
Invented the pocket
o Defining Corre
Errors in Experimental Measurements
o Sources of errors
Accuracy, precision, resolution
A mathematical model of errors
Confidence intervals
For means
For proportions
How many measurements are needed for desired error?
Why do we need statistics?
N
Chapter 10 Correlation and Regression
Learning objectives and outcomes
After this chapter, students will
Understand linear correlation and linear correlation coefficient
Understand positive correlation, negative correlation, no correlation and nolinear