OBJECTIVES
Demonstrate knowledge of statistical terms. Differentiate between the two branches of statistics. Identify types of data. Identify the measurement level for each variable. Identify the four basic sampling techniques. Explain the difference between an observational and an experimental study. Explain how statistics can be used and misused. Explain the importance of computers and calculators in statistics.

Statistics is the science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data. Descriptive statistics consists of the collection, organization, summarization, and presentation of data. Inferential statistics consists of generalizing from samples to populations, performing estimations hypothesis testing, determining relationships among variables, and making predictions. (Probability, Hypothesis testing, relationships between variables, predictions) Probability is the chance of an event occurring. A population consists of all subjects that are being studied. A sample is a group of subjects selected from a population.

Variables and Types of Data
In order to gain knowledge about seemingly haphazard events, statisticians collect information for variables that describe the events. A variable is a characteristic or attribute that can assume different values. Data are the values that variables can assume. A data set is a collection of data values. Each value in the data set is called a data value or a datum. Random variables have values that are determined by chance.

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Chapter 1 Nature of Probability and Statistics

Qualitative variables can be placed into distinct categories according to some characteristic or attribute. Quantitative variables are numerical in nature and can be ordered or ranked. Quantitative variables can be further classified into two groups. o Discrete variables assume values that can be counted. o Continuous...

...Perpetual Help System Dalta Molino Campus
Molino III, Bacoor City
Probability and Statistics
LAGERA, Einar John A.
Table of Contents
Simple Correlation Analysis ................................................................................................. 1
Introduction .................................................................................................................................................................. 1 What is Correlation? ............................................................................................................................................ 1 Discussion starts here(Simple Correlation Analysis) ................................................................................ 3 Calculating the Correlation ................................................................................................................................... 5 Sample Problem ......................................................................................................................................................... 5
Regression Analysis ................................................................................................................ 7
Introduction .................................................................................................................................................................. 7 What is this Regression...

...April, and a twelve-plus week break in the summer. However, the “Traditional Calendar” has not always been a tradition.
In other hand, the year-round calendar and any school adhering to the possesses many nomenclatural faces: Year-round calendars have been referred to as four quarter plans, continuous all year plans, four vacation plans, alternative calendar plans, mountain calendar plans, personalized calendar plans, community calendars, custom calendars, balanced calendars and the aforementioned modified school calendars.
In terms of academic achievement and implementation of an alternative school calendar is supposed to address one specific thing: something the literature calls “Summer Learning Loss”. According to an oft-cited “meta-analysis”, or quantitative review, of all then-previous research concerning Summer Learning Loss, Harris Cooper and his colleagues estimated that the typical child loses a bit more than one month’s amount of skill or knowledge in Math, Language Arts, and Reading combined during a typical, “traditional” summer break.
According to the research conducted by Nick Grinsted, He cited the study of Harris Cooper and his colleagues the effects of having classes during summer. They stated that student having classes during summer may experience Summer Learning Loss that causes them to lose a skill or knowledge in specific subjects like Math, Language and Arts and Reading during summer. If the proposed moving of opening of classes from...

...In this module we focus on a number of useful models and techniques that can be used in the
decision making process. Two important themes run through the study guide: data analysis and
decision making techniques.
Firstly we look at data analysis. This approach starts with data that are manipulated or processed
into information that is valuable to decision making. The processing and manipulation of raw
data into meaningful information are the heart of dataanalysis. Data analysis includes data
description, data inference, the search for relationships in data and dealing with uncertainty
which in turn includes measuring uncertainty and modelling uncertainty explicitly.
In addition to data analysis, other decision making techniques are discussed. These techniques
include decision analysis, project scheduling and network models.
Chapter 1 illustrates a number of ways to summarise the information in data sets, also known as
descriptive statistics. It includes graphical and tabular summaries, as well as summary measures
such as means, medians and standard deviations.
Uncertainty is a key aspect of most business problems. To deal with uncertainty, we need a basic
understanding of probability. Chapter 2 covers basic rules of probability and in Chapter 3 we
discuss the important concept of probability distributions in some...

...Data’s that are fundamentally amalgamated into scopes of miscalculations, randomized sampling as well as certainty periods. Such thoughts like these are statistical by nature without us even realizing it. To further explain statistics, it is a discipline that is made up regarding certain factors that involve things like deductive reasoning; granted, Science is practically statistics in and of itself through fabricating experimentations that require data collectivity, recapitulating information for the purpose of understanding something and pulling deductions through the use of the Scientific Method (i.e. formulating theories) through data collection. Sample Data Sample data basically is a subclass of populations such as humans, animals and even objects; it often goes as far as Physical Science and the Scientific Method. Within statistics, known as survey methodology, Sample Data concerns itself in the selective method regarding the subset of inhabitants or humans from within any particular population. This is done in order to approximate the uniqueness of an entire populace like weight, gender, color, religion, job types, etc. Sample Data surveying is also extremely cost effective opposed to surveying an entire
population. In short, this form of Sample Data is, from my own opinion, nothing more than probability theories. Population Data On the other hand, Population Data is just that; a means or...

...Programmes Division
Second Semester 2010-2011
Course Handout
Course Number
Course Title
: AAOC ZC111
: Probability and Statistics
Course E-mail address : aaoczc111@dlpd.bits-pilani.ac.in
Course Description
Probability spaces; conditional probability and independence; random variables and probability
distributions; marginal and conditional distributions; independent random variables, mathematical
exceptions, mean and variance, Binomial Poisson and normal distribution; sum of independent random
variables; law of large numbers; central limit theorem; sampling distributions; tests for mean using normal
and student’s distributions; tests of hypotheses; correlation and linear regression.
Scope and Objectives
At the end of the course, the student should be able to understand probabilistic & deterministic models and
statistical inference and apply these concepts to solve a variety of problems.
Prescribed Text Book
T1
Johnson Richard A. & C.B. Gupta, Miller & Freund’s Probability and Statistics for Engineers, PHI,
7th Ed., 2005.
Reference Books
R1.
Paul L. Meyer, Introductory Probability and Statistical Appl., Second Edition. Addison-Wesley, 1970.
R2. M.S. Radhakrishnan, Probability & Statistics, DLPD Notes Note: Softcopy of this Supplementary notes will
be available for download from BITS DLP website.
R3. Mendenhall Beaver Beaver,...

...Statistics is the study of the collection, organization, analysis, interpretation and presentation of data. It deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.
Descriptive statistics is the discipline of quantitatively describing the main features of a collection of information, or the quantitative description itself. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent.
Statistical inference is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation. Initial requirements of such a system of procedures for inference and induction are that the system should produce reasonable answers when applied to well-defined situations and that it should be general enough to be applied across a range of situations. Inferential statistics are used to test hypotheses and make estimations using sample data.
Variable (mathematics), a symbol that represents a quantity in a mathematical expression, as used in many sciences
Qualitative Variables or Categorical Variable
Also known as categorical variables, qualitative...

...attempt to gain an academic advantage in a dishonest or unfair manner. Breaches of the Academic Honesty Policy will result in dismissal from HCT
Project Objectives:
To estimate the population parameters from sample statistics, using interval estimate (90%, 95% and 99% levels).
The project consists of three parts as listed below. You should carefully read the instructions. This project is Group based (2 – 3) and each Group will have different results based on the initial data generated. Make sure to include all your work in the final report submitted. You will submit your final work (Report and Spreadsheet on Bb Learn)
PART I: Sample Generation- data presentation and data summary (25 )
1. Use the Data Set provided to you by your Instructor (No Two Groups can do the Same Dataset)
2. Write down a ‘Research Problem’ (Hypothesize a question about the data – what do you want to study- which variable(s)?) 4 points Age, blood pusher
3. Summarize and present the population (mean, variance and standard deviation) : 4 points
4. Select a sample from the data set: 6 points
a. Decide on the sample size 30
b. Decide on the sampling method
c. Clearly present the sample in an appropriate table. But it in table
5. Summarize your sample by finding sample statistics (mean, variance and standard deviation. 3 points
6. Present population and sample data graphically(histogram).4 points
7. Comment on the distribution shape and compare between...

...Organization of Terms
Experimental Design
Descriptive
Inferential
Population
Parameter
Sample
Random
Bias
Statistic
Types of
Variables
Graphs
Measurement scales
Nominal
Ordinal
Interval
Ratio
Qualitative
Quantitative
Independent
Dependent
Bar Graph
Histogram
Box plot
Scatterplot
Measures of
Center
Spread
Shape
Mean
Median
Mode
Range
Variance
Standard deviation
Skewness
Kurtosis
Tests of
Association
Inference
Correlation
Regression
Slope
y-intercept
Central Limit Theorem
Chi-Square
t-test
Independent samples
Correlated samples
Analysis-of-Variance
Glossary of Terms
Statistics - a set of concepts, rules, and procedures that help us to:
organize numerical information in the form of tables, graphs, and charts;
understand statistical techniques underlying decisions that affect our lives and well-being; and
make informed decisions.
Data - facts, observations, and information that come from investigations.
Measurement data sometimes called quantitative data -- the result of using some instrument to measure something (e.g., test score, weight);
Categorical data also referred to as frequency or qualitative data. Things are grouped according to some common property(ies) and the number of members of the group are recorded (e.g., males/females, vehicle type).
Variable - property of an object or event that can take on different values. For example,...

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