MATH 2311 Help Using R-Studio. To download R-Studio Go to the following link: Follow the instructions for your computer.

Slides:



Advertisements
Similar presentations
The Normal Distribution
Advertisements

Modular 12 Ch 7.2 Part II to 7.3. Ch 7.2 Part II Applications of the Normal Distribution Objective B : Finding the Z-score for a given probability Objective.
Modeling Process Quality
Total Population of Age (Years) of People that Smoke
 Catalogue No: BS-338  Credit Hours: 3  Text Book: Advanced Engineering Mathematics by E.Kreyszig  Reference Books  Probability and Statistics by.
Kate Schwartz & Lexy Ellingwood CHAPTER 8 REVIEW: THE BINOMIAL AND GEOMETRIC DISTRIBUTIONS.
Graphing Examples Categorical Variables
Lesson 6 – 2b Hyper-Geometric Probability Distribution.
L7.1b Continuous Random Variables CONTINUOUS RANDOM VARIABLES NORMAL DISTRIBUTIONS AD PROBABILITY DISTRIBUTIONS.
Normal Approximation Of The Binomial Distribution:
5-1 Business Statistics: A Decision-Making Approach 8 th Edition Chapter 5 Discrete Probability Distributions.
Using Normal Distribution to Approximate a Discrete Distribution.
Poisson Random Variable Provides model for data that represent the number of occurrences of a specified event in a given unit of time X represents the.
Binomial and Geometric Distributions Notes on your own paper.
 If E and F are two independent events with P(E)=.2 and P(F)=.4 find:  1) P(E|F)  2) P(F|E)  3) P(E∩F)  4) P(EUF)  1) ).083).52 WARM UP:
Normal Probability Distributions Larson/Farber 4th ed 1.
ENGR 610 Applied Statistics Fall Week 3 Marshall University CITE Jack Smith.
McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 6 Continuous Random Variables.
Discrete Probability Distributions. Random Variable Random variable is a variable whose value is subject to variations due to chance. A random variable.
Math b (Discrete) Random Variables, Binomial Distribution.
Total Population of Age (Years) of People. Pie Chart of Males and Females that Smoke Systematic Gender Sample Total Population: 32.
Statistics with TI-Nspire™ Technology Module E. Lesson 2: Properties Statistics with TI-Nspire™ Technology Module E.
© 2003 Prentice-Hall, Inc. Chap 5-1 Continuous Probability Distributions Continuous Random Variable Values from interval of numbers Absence of gaps Continuous.
MATH 4030 – 4B CONTINUOUS RANDOM VARIABLES Density Function PDF and CDF Mean and Variance Uniform Distribution Normal Distribution.
Chapter 3 – Graphical Displays of Univariate Data Math 22 Introductory Statistics.
§ 5.3 Normal Distributions: Finding Values. Probability and Normal Distributions If a random variable, x, is normally distributed, you can find the probability.
MATH 2400 Ch. 10 Notes. So…the Normal Distribution. Know the 68%, 95%, 99.7% rule Calculate a z-score Be able to calculate Probabilities of… X < a(X is.
Methodology Solving problems with known distributions 1.
Math 4030 Midterm Exam Review. General Info: Wed. Oct. 26, Lecture Hours & Rooms Duration: 80 min. Close-book 1 page formula sheet (both sides can be.
Ch. 15H continued. * -applied to experiments with replacement ONLY(therefore…..independent events only) * -Note: For DEPENDENT events we use the “hypergeometric.
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Chapter 11 Review Important Terms, Symbols, Concepts Sect Graphing Data Bar graphs, broken-line graphs,
Discrete and Continuous Random Variables. Yesterday we calculated the mean number of goals for a randomly selected team in a randomly selected game.
Chapter 6: Continuous Probability Distributions A visual comparison.
Geometric Distribution. The geometric distribution computes the probability that the first success of a Bernoulli trial comes on the kth trial. For example,
Normal Distributions.
Statistics with TI-Nspire™ Technology Module E Lesson 1: Elementary concepts.
Once again, my blog site is You should visit this site to get notes and assignments, check.
Chapter 31Introduction to Statistical Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012 John Wiley & Sons, Inc.
 I can identify the shape of a data distribution using statistics or charts.  I can make inferences about the population from the shape of a sample.
Statistics and Probability Theory Lecture 01 Fasih ur Rehman.
Chapter 6: Continuous Probability Distributions A visual comparison.
Unit 2 Test Topics: Statistics Honors Analysis. Conditional Probability Geometric Probability ◦ triangles ◦ triangles ◦Basic area formulas.
Unit 4 Review. Starter Write the characteristics of the binomial setting. What is the difference between the binomial setting and the geometric setting?
Chap 5-1 Chapter 5 Discrete Random Variables and Probability Distributions Statistics for Business and Economics 6 th Edition.
© 2003 Prentice-Hall, Inc. Chap 5-1 Continuous Probability Distributions Continuous Random Variable Values from interval of numbers Absence of gaps Continuous.
The Normal Model Chapter 6 Density Curves and Normal Distributions.
Cell Diameters and Normal Distribution. Frequency Distributions a frequency distribution is an arrangement of the values that one or more variables take.
MATH 2311 Help Using R-Studio. To download R-Studio Go to the following link: and
Statistical Quality Control, 7th Edition by Douglas C. Montgomery.
STAT 4030 – Programming in R STATISTICS MODULE: Basic Data Analysis
Chapter 1 A Review of Basic Concepts (Optional).
Math a Discrete Random Variables
Continuous Random Variables
STAT 206: Chapter 6 Normal Distribution.
MATH 2311 Section 1.5.
Standard Normal Calculations
Continuous Random Variables
Organizing and Displaying Data
HMI 7530– Programming in R STATISTICS MODULE: Basic Data Analysis
The Normal Probability Distribution Summary
Statistics: The Interpretation of Data
Means & Medians.
Use the graph of the given normal distribution to identify μ and σ.
@pbrucemaths Read the paper, annotate questions Check your answers!
Warm Up 4/30 What are you thankful for?
Continuous distribution curve.
The Normal Distribution
Statistical Models or Quality Control Improvement
MATH 2311 Section 1.5.
Presentation transcript:

MATH 2311 Help Using R-Studio

To download R-Studio Go to the following link: Follow the instructions for your computer operating system.

Basic Commands: Assign a data set to a variable: Type the following: assign(“x”,c(2,3,4,5)) This will assign the list: 2, 3, 4, 5 to the variable x.

Basic Commands: Assign a data set to a variable (method 2) Type the following: x<-c(2,3,4,5) This will assign the list: 2, 3, 4, 5 to the variable x.

Calculating Mean, Median, and Standard Deviation Once a list is assigned to variable, you can easily calculate mean, median and standard deviation: mean(x)min(x) median(x)max(x) sd(x)length(x) How many elements

Try it out! Calculate the mean, median, and standard deviation of the following: 4, 6, 10, 11, 13, 15, 16, 20

Graphs in R-Studio Histograms: hist(x) Boxplots: boxplot(x) Dot Plot: dotchart(x) Stem and Leaf: stem(x) Pie Chart: pie(x)

Probability Distributions To enter a Random Variable: assign(“x”,c(1,2,3,4,5)) assign(“p”,c(0.5,0.3,0.1,0.05,0.05) Where p(1)=0.5, etc. For the mean:sum(x*p) For the variance:sum((x-mean)^2*p)

Binomial Distributions For an exact value: dbinom(x,n,p) For cumulative values: x=0,1,2,…q pbinom(q,n,p)

Geometric Distributions For an exact value: dgeom(n-1,p) For cumulative values: x=0,1,2,…q pgeom(n-1,p)

Hypergeometric Distribution For an exact value: dhyper(success, possible success, sample size, selection) For successes going from 0 through highsuccess: phyper(highsuccess, possible success, sample size, selection)

Normal Curves To find the probability of an event occurring in a Normal Distribution pnorm(X,mean,standard deviation) This will return the probability of events 0 < k < X If you have a known probability to translate into a z-score: qnorm(probability)