MAT 135

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PUEBLO COMMUNITY COLLEGE

COURSE SYLLABUS

1.

course Title:

Introduction to Statistics

Prefix/Number:

MAT 135

Credit Hours:

3

2.

Prerequisites:

Successful completion of MAT 106 with a C or better or math assessment

3.

Resources Needed:

Text:

Essentials of Statistics, 3rd edition, Mario F. Triola

Supplies:

Pencil, paper, scientific calculator

4.

Course DESCRIPTION:

Includes data presentation and summarization, introduction to probability concepts and distributions, statistical inference --estimation, hypothesis testing, comparison of populations, correlation and regression.

5.

STANDARD COMPETENCIES:

A.

Have a working knowledge of and distinguish between the two branches of statistics, descriptive statistics and inferential statistics.

B.

Distinguish between qualitative and quantitative data.

C.

Distinguish between the following levels of measurement: nominal, ordinal, interval, and ratio.

D.

Define a population and sample.

E.

Define a parameter and statistic.

F.

Recognize that Greek letters are used to represent parameters and English letters are used to represent statistics.

G.

Present various methods of depicting data and statistical measures utilized in descriptive statistics.

H.

Organize data into a grouped frequency table.

I.

Present data in the form of histograms, stem and leaf diagrams, and/or box and whisker plots.

J.

Interpret histograms , line graphs, bar graphs, pie charts, and stem and leaf diagrams.

K.

Use formulas to calculate the following measures of central tendency: mean median, mode, and midrange.

L.

Use formulas to calculate the following measures of dispersion: range, variance, and standard deviation.

M.

Use the appropriate procedures to find the following measures of position in a set of data: z-score, percentile, quartile, and deciles.

N.

Define percentile and use this to interpret percentile ranks.

O.

Recognize and identify various shapes of data distributions.

P.

Utilize the basic definitions to calculate simple probabilities.

Q.

Utilize the addition rule to calculate probabilities for the occurrence of one event or the another event.

R.

Demonstrate an understanding of how events are are complementary and calculate the probability that an event does not occur.

S.

Use counting principles to determine the number of ways various events can occur.

T.

Develop the concepts of probability distributions.

U.

Distinguish between discrete and continuous random variables.

V.

Have a working knowledge of the concept of probability distributions.

W.

Use formulas to calculate the mean, variance, standard deviation, and expected value of a probability distribution.

X.

Calculate probabilities in binomial experiments.

Y.

Recognize and identify various shapes of probability distributions.

Z.

Demonstrate knowledge of the relationship between probability and the area under a probability curve.

AA.

Describe the normal distribution and the associated statistics and probabilities.

AB.

Determine probabilities using the standard normal curve.

AC.

Determine z-scores that correspond with observations in non-standard normal distributions.

AD.

Determine scores that correspond to given probabilities.

AE.

Use the normal distribution to approximate probabilities associated with a binomial experiment and know the conditions for which these approximations are appropriate.

AF.

Know the meaning of a sampling distribution.

AG.

Develop the concepts of point estimates and interval estimates and present methods for determining sample size.

AH.

Estimate the value of a population mean and determine confidence intervals for a population proportion.

AI.

Perform and analyze one-sample hypothesis tests for means and proportions.

AJ.

Perform two-sample hypothesis tests for means and proportions

AK.

Interpret scatter plots for paired data.

AL.

Compute and interpret Pearson's r for paired data.

AM.

Interpret the results of a regression analysis for paired data.

AN.

Perform and analyze Chi-square goodness-of fit tests.

AO.

Perform and analyze Chi-square tests of independence and homogeneity.

AP.

Perform and interpret one-way ANOVA tests.

6.

COURSE OUTLINE

1.0 Introduction to Statistics

1.1 Overview

1.2 Types of Data

1.3 Critical Thinking

1.4 Design of Experiments

2.0 Summarizing and Graphing Data

2.1 Overview

2.2 Frequency Distributions

2.3 Histograms

2.4 Statistical Graphics

3.0 Statistics for Describing, Exploring, and Comparing Data

3.1 Overview

3.2 Measures of Center

3.3 Measures of Variation

3.4 Measures of Relative Standing

3.5 Exploratory Data Analysis (EDA)

4.0 Probability

4.1 Overview

4.2 Fundamentals

4.3 Addition Rule

4.4 Multiplication Rule: Basics

4.5 Multiplication Rule: Complements and Conditional Probability

5.0 Discrete Probability Distributions

5.1 Overview

5.2 Random Variables

5.3 Binomial Probability Distributions

5.4 Mean, Variance and Standard Deviation for the Binomial Distribution

6.0 Normal Probability Distributions

6.1 Overview

6.2 The Standard Normal Distribution

6.3 Applications of Normal Distributions

6.4 Sampling Distributions and Estimators

6.5 The Central Limit Theorem

6.6 Normal as Approximation to Binomial

7.0 Estimates and Sample Sizes

7.1 Overview

7.2 Estimating a Population Proportion

7.3 Estimating a Population Mean: s Known

1.	course Title:	Introduction to Statistics
	Prefix/Number:	MAT 135	Credit Hours:	3
2.	Prerequisites:	Successful completion of MAT 106 with a C or better or math assessment

3.	Resources Needed:
	Text:	Essentials of Statistics, 3rd edition, Mario F. Triola
	Supplies:	Pencil, paper, scientific calculator

5.	STANDARD COMPETENCIES:
	A.	Have a working knowledge of and distinguish between the two branches of statistics, descriptive statistics and inferential statistics.
	B.	Distinguish between qualitative and quantitative data.
	C.	Distinguish between the following levels of measurement: nominal, ordinal, interval, and ratio.
	D.	Define a population and sample.
	E.	Define a parameter and statistic.
	F.	Recognize that Greek letters are used to represent parameters and English letters are used to represent statistics.
	G.	Present various methods of depicting data and statistical measures utilized in descriptive statistics.
	H.	Organize data into a grouped frequency table.
	I.	Present data in the form of histograms, stem and leaf diagrams, and/or box and whisker plots.
	J.	Interpret histograms , line graphs, bar graphs, pie charts, and stem and leaf diagrams.
	K.	Use formulas to calculate the following measures of central tendency: mean median, mode, and midrange.
	L.	Use formulas to calculate the following measures of dispersion: range, variance, and standard deviation.
	M.	Use the appropriate procedures to find the following measures of position in a set of data: z-score, percentile, quartile, and deciles.
	N.	Define percentile and use this to interpret percentile ranks.
	O.	Recognize and identify various shapes of data distributions.
	P.	Utilize the basic definitions to calculate simple probabilities.
	Q.	Utilize the addition rule to calculate probabilities for the occurrence of one event or the another event.
	R.	Demonstrate an understanding of how events are are complementary and calculate the probability that an event does not occur.
	S.	Use counting principles to determine the number of ways various events can occur.
	T.	Develop the concepts of probability distributions.
	U.	Distinguish between discrete and continuous random variables.
	V.	Have a working knowledge of the concept of probability distributions.
	W.	Use formulas to calculate the mean, variance, standard deviation, and expected value of a probability distribution.
	X.	Calculate probabilities in binomial experiments.
	Y.	Recognize and identify various shapes of probability distributions.
	Z.	Demonstrate knowledge of the relationship between probability and the area under a probability curve.
	AA.	Describe the normal distribution and the associated statistics and probabilities.
	AB.	Determine probabilities using the standard normal curve.
	AC.	Determine z-scores that correspond with observations in non-standard normal distributions.
	AD.	Determine scores that correspond to given probabilities.
	AE.	Use the normal distribution to approximate probabilities associated with a binomial experiment and know the conditions for which these approximations are appropriate.
	AF.	Know the meaning of a sampling distribution.
	AG.	Develop the concepts of point estimates and interval estimates and present methods for determining sample size.
	AH.	Estimate the value of a population mean and determine confidence intervals for a population proportion.
	AI.	Perform and analyze one-sample hypothesis tests for means and proportions.
	AJ.	Perform two-sample hypothesis tests for means and proportions
	AK.	Interpret scatter plots for paired data.
	AL.	Compute and interpret Pearson's r for paired data.
	AM.	Interpret the results of a regression analysis for paired data.
	AN.	Perform and analyze Chi-square goodness-of fit tests.
	AO.	Perform and analyze Chi-square tests of independence and homogeneity.
	AP.	Perform and interpret one-way ANOVA tests.
6.	COURSE OUTLINE
	1.0 Introduction to Statistics
		1.1 Overview
		1.2 Types of Data
		1.3 Critical Thinking
		1.4 Design of Experiments
	2.0 Summarizing and Graphing Data
		2.1 Overview
		2.2 Frequency Distributions
		2.3 Histograms
		2.4 Statistical Graphics
	3.0 Statistics for Describing, Exploring, and Comparing Data
		3.1 Overview 3.2 Measures of Center 3.3 Measures of Variation 3.4 Measures of Relative Standing 3.5 Exploratory Data Analysis (EDA)
	4.0 Probability
		4.1 Overview
		4.2 Fundamentals
		4.3 Addition Rule
		4.4 Multiplication Rule: Basics
		4.5 Multiplication Rule: Complements and Conditional Probability
	5.0 Discrete Probability Distributions
		5.1 Overview
		5.2 Random Variables
		5.3 Binomial Probability Distributions
		5.4 Mean, Variance and Standard Deviation for the Binomial Distribution
	6.0 Normal Probability Distributions
		6.1 Overview
		6.2 The Standard Normal Distribution
		6.3 Applications of Normal Distributions
		6.4 Sampling Distributions and Estimators
		6.5 The Central Limit Theorem
		6.6 Normal as Approximation to Binomial
	7.0 Estimates and Sample Sizes
		7.1 Overview
		7.2 Estimating a Population Proportion
		7.3 Estimating a Population Mean: s Known