# Register now to access 7 million high quality study materials (What's Course Hero?) Course Hero is the premier provider of high quality online educational resources. With millions of study documents, online tutors, digital flashcards and free courseware, Course Hero is helping students learn more efficiently and effectively. Whether you're interested in exploring new subjects or mastering key topics for your next exam, Course Hero has the tools you need to achieve your goals.

5 Pages

### day4

Course: STAT 218, Fall 2009
School: Cal Poly
Rating:

Word Count: 440

#### Document Preview

218 Stat - Day 4 Five-number summary, Boxplots Five-number summary (FNS): Minimum, Lower Quartile (Q1), Median, Upper Quartile (Q3), Maximum Quartiles are calculated as the median of the values below/above the location of the actual median Example: Natural selection (Bumpus) Humerus lengths (inches) of sparrows who survived storm (n=35): 0.687 0.728 0.739 0.752 0.659 0.726 0.744 0.703 0.728 0.741 0.755 0.689 0.729...

Register Now

#### Unformatted Document Excerpt

Coursehero >> California >> Cal Poly >> STAT 218

Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.

Course Hero has millions of student submitted documents similar to the one below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
218 Stat - Day 4 Five-number summary, Boxplots Five-number summary (FNS): Minimum, Lower Quartile (Q1), Median, Upper Quartile (Q3), Maximum Quartiles are calculated as the median of the values below/above the location of the actual median Example: Natural selection (Bumpus) Humerus lengths (inches) of sparrows who survived storm (n=35): 0.687 0.728 0.739 0.752 0.659 0.726 0.744 0.703 0.728 0.741 0.755 0.689 0.729 0.745 0.709 0.729 0.741 0.756 0.702 0.731 0.752 0.715 0.730 0.741 0.766 0.703 0.736 0.752 0.721 0.730 0.741 0.767 0.709 0.737 0.754 0.723 0.733 0.743 0.769 0.713 0.738 0.765 0.723 0.733 0.749 0.770 0.720 0.738 0.726 0.735 0.751 0.780 0.720 0.739 0.728 0.736 0.752 Humerus lengths of sparrows who perished in storm (n=24): 0.726 0.743 (a) Find FNS of humerus lengths for sparrows who survived the storm. (b) Find FNS of humerus lengths for sparrows who did not survive the storm. Boxplot: visual representation of FNS (c) Produce (unmodified) boxplots to compare these distributions. (d) Compare and contrast the two distributions of humerus lengths. Modified boxplot: indicates outliers separately, extends whisker to most extreme non-outlier. Outliers are values more than 1.5*(Q3-Q1) from nearer quartile (e) Check for outliers in both groups. (f) Create modified boxplots of humerus lengths for the two groups. (g) Use Minitab (bumpus.mtw) to reproduce this analysis. [Notes: The data are presented in unstacked format in c1 and c2, meaning that each group has its own column. The data are presented in stacked format in c4 and c5, meaning that all of the data are in one column with a separate column indicating the group variable. You can use Graph> Boxplot and then choose one Y, with groups with the stacked data or multiple Ys, simple with the unstacked data. Also, be aware that Minitab may calculate quartiles a bit differently.] Example: Draft lottery The following data are the draft numbers (1-366) assigned to birthdates in the 1970 draft lottery. Men born on the date assigned a draft number of 1 were the first to be drafted, followed by those born on the date assigned draft number 2, and so on. Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Jan 305 159 251 215 101 224 306 199 194 325 329 221 318 238 17 121 235 140 58 280 186 337 118 59 52 92 355 77 349 164 211 Feb 86 144 297 210 214 347 91 181 338 216 150 68 152 4 89 212 189 292 25 302 363 290 57 236 179 365 205 299 285 Mar 108 29 267 275 293 139 122 213 317 323 136 300 259 354 169 166 33 332 200 239 334 265 256 258 343 170 268 223 362 217 30 Apr 32 271 83 81 269 253 147 312 219 218 14 346 124 231 273 148 260 90 336 345 62 316 252 2 351 340 74 262 191 208 May 330 298 40 276 364 155 35 321 197 65 37 133 295 178 130 55 112 278 75 183 250 326 319 31 361 357 296 308 226 103 313 Jun 249 228 301 20 28 110 85 366 335 206 134 272 69 356 180 274 73 341 104 360 60 247 358 109 137 22 64 222 353 209 Jul 93 350 115 279 188 327 50 13 277 284 248 15 42 331 322 120 98 190 227 187 27 153 172 23 67 303 289 88 270 287 193 Aug 111 45 261 145 54 114 168 48 106 21 324 142 307 198 102 44 154 141 311 344 291 339 116 36 286 245 352 167 61 333 11 Sep 225 161 49 232 82 6 8 184 263 71 158 242 175 1 113 207 255 246 177 63 204 160 119 195 149 18 233 257 151 315 Oct 359 125 244 202 24 87 234 283 342 220 237 72 138 294 171 254 288 5 241 192 243 117 201 196 176 7 264 94 229 38 79 Nov 19 34 348 266 310 76 51 97 80 282 46 66 126 127 131 107 143 146 203 185 156 9 182 230 132 309 47 281 99 174 Dec 129 328 157 165 56 10 12 105 43 41 39 314 163 26 320 96 304 128 240 135 70 53 162 95 84 173 78 123 16 3 100 (a) What draft number was assigned to your birthday? Is this draft number in the top third, middle third, or last third of the draft order? The following table arranges in order the draft numbers for each month: Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Jan 17 52 58 59 77 92 101 118 121 140 159 164 186 194 199 211 215 221 224 235 238 251 280 305 306 318 325 329 337 349 355 Feb 4 25 57 68 86 89 91 144 150 152 179 181 189 205 210 212 214 216 236 285 290 292 297 299 302 338 347 363 365 Mar 29 30 33 108 122 136 139 166 169 170 200 213 217 223 239 256 258 259 265 267 268 275 293 300 317 323 332 334 343 354 362 Apr 2 14 32 62 74 81 83 90 124 147 148 191 208 218 219 231 252 253 260 262 269 271 273 312 316 336 340 345 346 351 May 31 35 37 40 55 65 75 103 112 130 133 155 178 183 197 226 250 276 278 295 296 298 308 313 319 321 326 330 357 361 364 Jun 20 22 28 60 64 69 73 85 104 109 110 134 137 180 206 209 222 228 247 249 272 274 301 335 341 353 356 358 360 366 Jul 13 15 ...

Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more. Course Hero has millions of course specific materials providing students with the best way to expand their education.

Below is a small sample set of documents:

Cal Poly - STAT - 322
Guide to MinitabDr. Jimmy Doi1Introduction to MinitabMinitab is a statistical analysis software package. The software is freely available to all students and is downloadable through the Technology Tab at my.calpoly.edu. When you rst launch Mi
Cal Poly - STAT - 330
Supplement: The IN= StatementStat 330, Dr. Jimmy A. DoiSupplement: The IN= StatementThis supplement is oered in response to a question a few students raised with regard to the IN= statement. Please refer to the course notes/textbook for more det
Cal Poly - STAT - 218
Ch. 7 Addendum: Using MinitabStat 218, Dr. Jimmy A. DoiAdditional Notes for Minitab Please add to the current Guide to MinitabExercise (A) from Course Notes: Researchers suspect that the exposure to toluene will increase the levels of NE in the
Cal Poly - STAT - 330
Supplement: The LAG StatementStat 330, Dr. Jimmy A. DoiSupplement: The LAG StatementThis supplement is oered in response to a question a student raised with regard to the lag statement. Please refer to the course notes/textbook for more details
Cal Poly - STAT - 330
Supplement: Permanent Data SetsStat 330, Dr. Jimmy A. DoiSupplement: SAS Permanent Data SetsSuppose we want to import the raw data le age salary.txt which is stored at C:/mySAS/raw data/age salary.txt. Notice that the data is based on three vari
Cal Poly - STAT - 330
OPTIONS FORMCHARStat 330, Dr. Jimmy A. DoiOPTIONS FORMCHARHeres a tip from Professor Russ Lenth (Statistics Department, University of Iowa): How to make SAS tables/output print correctly SAS is set up to use its own fonts, and this causes annoyi
Cal Poly - STAT - 330
SAS Installation Guide Dr. Jimmy Doi, Statistics Dept. Cal Poly State University San Luis ObispoNOTE FOR WINDOWS VISTA USERS: If you are running WINDOWS VISTA (HOME or HOME DELUXE), please consult with the instructor DO NOT ATTEMPT TO INSTALL SAS
Cal Poly - STAT - 330
1STAT 330Reading Multiple Lines of Data per Observation Typically data sets consist of one observation per line SAS will go to the next line if it runs out of data before it has read all variables from the input statement Better if you tell SA
Cal Poly - STAT - 330
12STAT 330Keeping Track of Stats Can use out= option with most proc's to keep your statistics in a SAS data set useful for presentation or reporting can manipulate these statistics if need be in most procs (such as means) out= goes in an ou
Cal Poly - STAT - 330
STAT 330Lecture Set 12 - Bells and WhistlesOutput Delivery System (ODS) Prior to version 7 SAS output was designed for a traditional line-printer limited to monospace fonts and not as flexible Version 7 and up now contain the ODS Where do we
Cal Poly - STAT - 330
12STAT 330PROC CHART Proc CHART is used to generate bar charts Choose between vertical bars (vbar) and horizontal bars (hbar) vbar and hbar options include:Lecture Set 9 - Basic Statistical PROCsmidpoints = list - specifies midpoints for
Cal Poly - STAT - 330
1STAT 330Lecture Set 9 - Basic Statistical PROCs2PROC CHART Proc CHART is used to generate bar charts Choose between vertical bars (vbar) and horizontal bars (hbar) vbar and hbar options include:midpoints = list - specifies midpoints for
Cal Poly - STAT - 330
STAT 330Lecture Set 13 - Useful things to knowDynamic Data Exchange (DDE) Recall that we used DDE to read data into SAS from Excel We can use a similar method to dump data back into excel (and word) Useful for creating specialized data files a
Cal Poly - STAT - 330
12STAT 330Macros Macros allow you to write piece of code to be used over and over throughout your program very useful as this cuts down on the size of your programLecture Set 11 - Macro Concepts Macros used to be considered an advanced t
Cal Poly - STAT - 330
12STAT 330Basic PROCsLecture Set 7 - Basic PROCs All PROCs have required statements and optional statements Most PROCs make some sort of report or analysis By default will send output to output (listing) window34PROC SORTPROC SORT
Cal Poly - STAT - 330
STAT 330Dynamic Data Exchange (DDE) Recall that we used DDE to read data into SAS from Excel We can use a similar method to dump data back into excel (and word) Useful for creating specialized data files as well as making reports Some work requ
Cal Poly - STAT - 330
STAT 330Output Delivery System (ODS) Prior to version 7 SAS output was designed for a traditional line-printer limited to monospace fonts and not as flexible Version 7 and up now contain the ODS Lecture Set 12 - Bells and Whistles Where do we
Cal Poly - STAT - 330
Stat 330: Assignment 3 Due: Wednesday, January 21, 2009 at 11:59:59 pm1. Forbes is an American publishing and media company that is famous for its lists including the list of richest Americans, billionaires, and the most powerful celebrities. The r
Cal Poly - STAT - 330
12STAT 330Assignments A quick note about programs. For each assignment youwill be required to include the following information at the top of your program(s):* Name: Your Name(s); * Assignment: Assignment #; * Due Date: Due date from assignm
Cal Poly - STAT - 330
Stat 330: Assignment 1 Due: Wednesday, January 7, 2009 at 4:00 PM SAS offers help manuals in html format on the web. These web pages are superior to the standard help menu offered with the SAS software installation. If you cant find what you are look
Cal Poly - STAT - 330
12STAT 330Range Lists There are some handy shortcuts for listing variables Numbered range lists are for variables that start with the same characters and end with consecutive numbering Var6 Var7 Var8 is the same as Var6-Var8Lecture Set 5
Cal Poly - STAT - 330
Stat 330: Assignment 4 Due: Wednesday, January 28, 2009 at 11:59:59 pm 1. A company that works with various military contracts (too confidential to even be discussed in detail here) has a data file that contains basic contract initiation information
Cal Poly - STAT - 330
Stat 330: Assignment 2 Due: Wednesday, January 14, 2009 at 11:59:59 pm1. Data were collected on prices in cents per pound received by fishermen and vessel owners for various species of fish and shellfish in 1970 and 1980. The variables in this file
Cal Poly - STAT - 330
1STAT 330Lecture Set 6 Reading Data IIReading Multiple Lines of Data per Observation Typically data sets consist of one observation per line SAS will go to the next line if it runs out of data before it has read all variables from the input
Cal Poly - STAT - 330
1STAT 330Lecture Set 10 More Statistical PROCs2Keeping Track of Stats Can use out= option with most proc's to keep your statistics in a SAS data set useful for presentation or reporting can manipulate these statistics if need be in most
Cal Poly - STAT - 330
12STAT 330Administrative - GeneralLecture Set 1 Goals of course and SAS overview Website: http:/statweb.calpoly.edu/rottesen Office hours Homework Email to: STAT330HW@yahoo.com Labs Quizzes and Groupwork Projects Exams Working toge
Cal Poly - STAT - 330
1STAT 330Lecture Set 8 - Back to the DATA Step2SAS Automatic Variables We already know about automatic variables such as _N_ and _ERROR_ SAS can also create additional automatic variables under certain circumstances When using a by state
Cal Poly - STAT - 330
12STAT 330Drop/Keep It is not always necessary to keep all the variables in a data set Lecture Set 4 How Does SAS Process Data? and a do loop extravaganza sometimes better to only hang on to what is needed for reporting/analysis Use a dro
Cal Poly - STAT - 218
12STAT 218Sampling DistributionsLecture Set 4 Sampling Distributions Definition: Sampling Variability is the variability among random samples from the same population. A probability distribution that characterizes some aspect of sampling
Cal Poly - STAT - 218
Sampling Distributions Definition: Sampling Variability is the variability among random samples from the same population.A probability distribution that characterizes some aspect of sampling variability is calledThe Meta-Experiment A meta-experim
Cal Poly - STAT - 218
12STAT 218ApplicationLecture Set 8 More on the T Test and the Wilcoxon-Mann-Whitney TestExample: Nine observations of surface soil pH were made two different locations. Does the data suggest that the true mean soil pH values differ for the
Cal Poly - STAT - 218
12STAT 218Probability Probability is important to statistics because: study results can be influenced by variation it provides theoretical groundwork for statistical inferenceLecture Set 3 Random Sampling, Probability, and the Normal Dis
Cal Poly - STAT - 218
1STAT 218Statistical Inference Concerning 1 How can we use statistical inference in regression?2Lecture Set 13 More Regression Suppose we would like to investigate the relationship between X and Y If X is telling us nothing about Y, wha
Cal Poly - STAT - 218
12STAT 218Quantitative DataLecture Set 5 Sampling Distribution for the Mean and Introduction to Confidence Intervals More complex than dichotomous data Sample and populations for quantitative data can be described in various ways: mean, m
Cal Poly - STAT - 218
1STAT 218Planning a Study to Estimate It is important before you begin collecting data to consider whether the estimates will be sufficiently precise. Two factors to consider:2Lecture Set 6 Sample Size Calculations and Confidence Interval
Cal Poly - STAT - 218
Two Way ANOVA Name the type of two way ANOVA discussed in our text book.What is the point of blocking?Can blocks consist of more than two observations?Name the three parts that the total variability is split into.Completely RandomizedSS(betw
Cal Poly - STAT - 217
12STAT 217Measures of Center Recall that center is #2 of the BIG three. Measures of center for numerical data include: the mean the median the mode (the value with the highest frequency)Lecture Set 4 Center and Spread These measures a
Cal Poly - STAT - 217
Comparative Bar Chars What is the main purpose of a comparative bar chart?Example: According to the Cal Poly Fact Book 2003-2004 the enrollment by gender and college are as follows.Chart of Enrollment vs College, Gender90Percent of Enrollment
Cal Poly - STAT - 217
Name: STAT 217 HW addition Chapter 5 1. Consider the following data collected on the yield (in bushels) for 19 equal sized plots planted in tomatoes for that were sprayed with different amounts of fertilizer. Amount of Fertilizer (pounds per plot) 25
Cal Poly - STAT - 217
12STAT 217Planning a Study Before we analyze data, much thought and planning should go into how to collect the data Without quality information our conclusions will not mean muchLecture Set 2 Sampling and Design Six steps of the data ana
Cal Poly - STAT - 217
Choose the appropriate scenario: independent, paired, chi-square/goodness of fit, chi-square/contingency table, Oneway ANOVA, Two-way ANOVA, or regression. Is Friday the 13th an unusually unlucky day, or is this just superstition? How do superstition
Cal Poly - STAT - 217
Name: STAT 217 HW addition Chapter 8 1. The serum cholesterol of a population of 18-year-olds is approximately normally distributed with a mean of 176 mg/dLi and a standard deviation of 30 mg/dLi. What percentage of the 18-year-olds have a serum chol
Cal Poly - STAT - 217
Name: STAT 217 HW addition Chapter 151. The following ANOVA table is only partially completed. a. Complete the table.6Plot A5Individual Value PlotSource Treatment Error TotalDF 2SSMS 46.67F _P 0.0004330.00 1421 A B Cb.
Cal Poly - STAT - 217
Name: STAT 217 HW addition Chapters 3 and 41.For the following histograms, estimate the mean and median.Histogram of C114 12 10Histogram of C235 30 25 Frequency 20 15 10 5Frequency8 6 4 2 036424854 C1606672780012
Cal Poly - STAT - 217
Name: STAT 217 HW addition Chapter 4 1. Which of the boxplots below is represented by the histogram? Justify your answer.Boxplot of 1, 2, 3, 412 1 10 2 8 6 4 2 0Histogram3401020 Data304050Frequency01020 230402.Whic
Cal Poly - STAT - 217
Sampling Variability Do we expect that the sample mean x from a random sample will be exactly equal to the population mean ? ExplainWhat if we gathered another random sample of the same size, would this x be exactly equal to ? Explain.Would the
Cal Poly - STAT - 217
12STAT 217Basic Probability We typically think of probability as the chance that an event will occur Probability plays an important role in statistics because it allows us to make decisions with confidence We can think of probability as the
Cal Poly - STAT - 217
Statistics Example What do you think of when you hear statistics?What are three important reasons to learn statistics?Definition: Statistics is the scientific discipline that provides methods to help us make sense of data. To utilize statistics w
Cal Poly - STAT - 217
12STAT 217One Variable Categorical Data So far our experience with hypothesis testing and categorical data is limited to one dichotomous variable We need to expand our thinking to deal with more than two categories The Chi Square Goodness of
Cal Poly - STAT - 217
12STAT 217Correlation Analyze the relationship, if any, between variables x and y by examining the linear strength between them Correlation is a numerical measure of this linear relationshipLecture Set 5 Summary of Bivariate Data can be
Cal Poly - STAT - 217
DISCLAIMER: The size and question content of this review should not be considered an exact replication of the exam. The questions on the exam will be different. The purpose here is to supply you with more questions to practice with. In my opinion the
Cal Poly - STAT - 217
National paper company must purchase a new machine for producing cardboard boxes. The company must choose between two machines, machine 1 and machine 2. Since both machines produce boxes of equal quality, the company would like to choose the new mach
Cal Poly - STAT - 217
One Variable Categorical Data What does one sample data mean?What type of test would we use to compare a categorical variable with more than two groups?What does k stand for?Goodness of Fit Test What are the general forms of the hypotheses? Ho:
Cal Poly - STAT - 217
12STAT 217Comparison of Two Independent Samples Many times it is useful to compare two groups Male vs. Female Drug vs. PlaceboLecture Set 9 Comparison of Two Samples1 1Population 1x1 s1Sample 1 Size n12 2Population 2x2 s2Sampl
Cal Poly - STAT - 217
NOTE: The length of this review has nothing to do with the length of the final. I just wanted to give you a variety of questions to practice with. Please note that I focused on Chapters 11 to 15 because it is what we have covered most recently. It wo
Cal Poly - STAT - 217
Correlation What does correlation measure?If the correlation is negative what does this mean about x and y?If the correlation is positive what does this mean about x and y?Give an example of two variables that could be negatively correlated.G
Cal Poly - STAT - 217
12STAT 217Hypothesis Testing The idea of a hypothesis test is to formulate a hypothesis that nothing is going on and then to see if collected data is consistent with this hypothesis (or if the data shows something different)Lecture Set 8 Si
Cal Poly - STAT - 217
Hypothesis Testing Explain the idea behind a hypothesis test.Identify the main parts of a hypothesis test: 1. 2. 3. 4. Hypothesis Testing: #1 The hypotheses (#1) There are two types of hypotheses: 1. 2. notation: notation:In a single sample hypot
Cal Poly - STAT - 217
12STAT 217Administrative - General Website: http:/statweb.calpoly.edu/rottesen Office hours Homework, Quizzes and ActivitiesLecture Set 1 Goals of Course and Intro to Statistics Exams and Final Working together This class moves really
Cal Poly - STAT - 312
California Polytechnic State University, San Luis Obispo Summer 2007 Statistics 312/542: Statistical Methods for EngineersSTAT 312-01: MTWR 10:10-12:00, Room 20-140Instructor: Office: Phone: Email: Web Page: Office Hours: Monday 12:30-1:30 Text: We
Cal Poly - STAT - 330
Lecture 7In-Class Exam 1Lecture07.docSTAT 330Page 1 of 1