2011-Psych 60-Lecture 4

2011-Psych 60-Lecture 4 - 4/4/11 Announcements Virtual...

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Unformatted text preview: 4/4/11 Announcements Virtual Office Hours Virtual Office Hours Monday Ashtyn: 12:00pm 1:00pm Ryan: 2:00pm 3:00pm Jon: 11:00am 12:00pm Tristan: 1:00pm 2:00pm Jarita: 10:00am 11:00am Daniel: 6:00pm 7:00pm Joyce: 9:00am 10:00am Announcements Virtual Office Hours Tuesday Wednesday Thursday Saturday 1 4/4/11 Announcements Virtual Office Hours Materials for exams Announcements Virtual Office Hours Materials for exams Lecture Errata Errata Evidence supporNng Einstein's General Theory of RelaNvity "Red ShiS" is not accurate 2 4/4/11 Last Time Philosophy of Science Research Methods in Psychology 3 4/4/11 This Week Today Visual Displays of Data Measures of Central Tendency Measures of Variability Clicker IntroducNon and Try-out Visual Displays of Data Turn on your clicker 4 4/4/11 Turn on your clicker Try Out Your Clicker What year in college are you? A B C D E Freshman Sophomore Junior Senior Other Try Out Your Clicker Why are you taking this class? Try Out Your Clicker Which would you rather have? A B C D E Required for your major ElecNve in your major Not required, but I love StaNsNcs so I'm happy to be here! Not required, and I hate StaNsNcs, but I am a masochist so I'm happy to be here! Other A B C D An Apple iPhone A Google Android Smartphone A Windows Smartphone No Preference 5 4/4/11 Registering Your Clicker Registering Your Clicker hgp://www.iclicker.com/ need to register once each academic year Registering Your Clicker Registering Your Clicker 6 4/4/11 Registering Your Clicker Registering Your Clicker Use WebCT User Name Registering Your Clicker Registering Your Clicker 7 4/4/11 Visual Displays of Data FR O BE M FO RE Discrete vs. ConNnuous Discrete variables consists of separate categories where no values exist between neighboring categories (e.g. gender, number of children, whole-number age in years) ConNnuous variables have a (theoreNcally) infinite number of values falling between any two observed values (e.g. actual age in years, distance, Nme) 8 4/4/11 FR BE OM FO RE Nominal Ordinal Interval/RaNo a nominal scale consists of a set of categories that have different names. an ordinal scale consists of a set of categories that are organized in an ordered sequence e.g. gender, poli=cal ideology e.g. finishing place in race, Clothing sizes (S,M,L,XL) Olympic medals interval and ra=o scales consists of a series of ordered categories where the categories form intervals of the same size. Ra=o scales have a meaningful zero point e.g. distance, weight, temperature* Axes 2 2 1 1 0 0 9 4/4/11 Axes 2 Y Axis 2 1 Axes 1 0 0 X Axis X Axis Y Axis 2 1 Y Axis 20 18 16 14 12 10 8 6 4 2 0 Scale 0 X Axis X Axis 10 4/4/11 Y Axis 20 18 16 14 12 10 8 6 4 2 0 Scale Y Axis 20 18 16 14 12 10 8 6 4 2 0 X Axis X Axis Y Axis 20 18 16 14 12 10 8 6 4 2 0 Axis Label Frequency Y Axis 20 18 16 14 12 10 8 6 4 2 0 Frequency X Axis X Axis 11 4/4/11 Y Axis 20 18 16 14 12 10 8 6 4 2 0 Y Axis 20 18 16 14 12 10 8 6 4 2 0 Number of Cats X Axis Exam Score X Axis Bar Chart Line Chart Frequency DistribuNons Bar Chart Line Chart Frequency DistribuNons Scager plots Scager plots 12 4/4/11 Bar Charts A chart in which the lengths of bars are proporNonal to the values they represent Trillions of Dollars Gross Domes7c Product by Country (2004) 14 12 10 8 6 4 2 Most Appropriate For: Discrete data with a nominal or ordinal scale 0 Canada France Germany Italy Country Japan UK USA 13 4/4/11 Bar Chart Line Chart Frequency DistribuNons Bar Chart Line Chart Frequency DistribuNons Scager plots Scager plots Line Charts A chart in which the height of the line is proporNonal to the value at that point Most Appropriate For: Discrete data with an interval raNo scale 14 4/4/11 Gross DomesNc Product Gross Domes7c Product by Country (2004) 14 12 Trillions of Dollars Trillions of Dollars Gross Domes7c Product by Country (2004) 14 12 10 8 6 4 2 0 10 8 6 4 2 0 Canada France Germany Italy Country Japan UK USA Canada France Germany Italy Country Japan UK USA 15 4/4/11 Gross Domes7c Product by Country (2004) 14 12 Trillions of Dollars 10 8 6 4 2 0 Canada France Germany Italy Country Japan UK USA Check Your Understanding A researcher has collected data on people's liking for different fruit such as apples, oranges, and pineapples. She wants to graph the average raNng for each fruit. What type of chart is most appropriate? Check Your Understanding A researcher has collected data on people's liking for different fruit such as apples, oranges, and pineapples. She wants to graph the average raNng for each fruit. What type of chart is most appropriate? A B C A bar chart A line chart Either a line chart or bar chart A B C A bar chart A line chart Either a line chart or bar chart 16 4/4/11 Bar Chart Line Chart Frequency DistribuNons Scager plots Scager plot Bar Chart Line Chart Frequency DistribuNons A plot in which the locaNons of points in X and Y space represent the values for those points measured on two different variables Most Appropriate For: Scager plots ConNnuous or discrete data with both variables of interval or raNo scale 17 4/4/11 Student Tom Joe Meg Daphne Gloria Jeff Study Hours/Week 11 3 9 5 1 7 Final Grade 91 77 90 80 75 85 Scager Plot Scager Plot Student Tom Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Y-Axis X-Axis Joe Meg Daphne Gloria Jeff 18 4/4/11 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 19 4/4/11 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 20 4/4/11 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 21 4/4/11 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 22 4/4/11 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 23 4/4/11 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 Student Tom Joe Meg Daphne Gloria Jeff Hours 11 3 9 5 1 7 Grade 91 77 90 80 75 85 24 4/4/11 RelaNonship of Parent and Child Heights Bar Chart Line Chart Frequency DistribuNons Bar Chart Line Chart Frequency DistribuNons Scager plots Scager plots 25 4/4/11 Frequency DistribuNons Frequency DistribuNon Table Graphical displays of the frequencies of parNcular outcomes Types of Frequency DistribuNons Frequency DistribuNon Graph Grouped Frequency DistribuNon Table Grouped Frequency DistribuNon Graph Frequency distribuNon graphs are oSen called histograms, especially when displaying frequencies for conNnuous data Frequency DistribuNon Table Cups of Coffee Consumed Each Day N = 10 Individuals Types of Frequency DistribuNons Frequency DistribuNon Graph Grouped Frequency DistribuNon Table Grouped Frequency DistribuNon Graph 2, 4, 3, 4, 2, 3, 1, 0, 2, 1 26 4/4/11 Frequency DistribuNon Table Cups f Frequency DistribuNon Table Cups f 1. Add in values found in data including values for which the frequency is 0 Frequency DistribuNon Table Cups 4 3 2 1 0 f 1. Add in values found in data including values for which the frequency is 0 Frequency DistribuNon Table Cups 4 3 2 1 0 f 27 4/4/11 Frequency DistribuNon Table Cups 4 3 2 1 0 f 2. Enter the frequency of each value Frequency DistribuNon Table Cups 4 3 2 1 0 f 2 2 3 2 1 2. Enter the frequency of each value Frequency DistribuNon Table Cups 4 3 2 1 0 f 2 2 3 2 1 Frequency DistribuNon Table Cups 4 3 2 1 0 f 2 2 3 2 1 p = f/N 3. If proporNons are desired, take each frequency and divide by the total sample size 28 4/4/11 Frequency DistribuNon Table Cups 4 3 2 1 0 f 2 2 3 2 1 p = f/N 2/10 = .20 2/10 = .20 3/10 = .30 2/10 = .20 1/10 = .10 Frequency DistribuNon Table Cups 4 3 2 1 0 f 2 2 3 2 1 p .20 .20 .30 .20 .10 Frequency DistribuNon Table Frequency DistribuNon Table Types of Frequency DistribuNons Frequency DistribuNon Graph Grouped Frequency DistribuNon Table Grouped Frequency DistribuNon Graph Types of Frequency DistribuNons Frequency DistribuNon Graph Grouped Frequency DistribuNon Table Grouped Frequency DistribuNon Graph 29 4/4/11 Frequency DistribuNon Graph 4 3 2 1 0 0 1 2 3 4 4 3 2 1 0 Frequency DistribuNon Graph 0 1 2 3 4 Frequency DistribuNon Graph 4 3 4 3 Frequency DistribuNon Graph 1. Label x and y axis f 2 1 0 0 1 2 3 4 f 2 1 0 0 1 2 3 4 Cups of Coffee Cups of Coffee 30 4/4/11 Frequency DistribuNon Graph 4 3 Frequency DistribuNon Graph 4 3 2. Draw in bars with height equal to frequency for each category 2. Draw in bars with height equal to frequency for each category f 2 1 0 0 1 2 3 4 f 2 1 0 0 1 2 3 4 Cups of Coffee Cups of Coffee Frequency DistribuNon Graph 4 3 Frequency DistribuNon Graph 4 3 2. Draw in bars with height equal to frequency for each category 2. Draw in bars with height equal to frequency for each category f 2 1 0 0 1 2 3 4 f 2 1 0 0 1 2 3 4 Cups of Coffee Cups of Coffee 31 4/4/11 Frequency DistribuNon Graph 4 3 Frequency DistribuNon Graph 4 3 2. Draw in bars with height equal to frequency for each category 2. Draw in bars with height equal to frequency for each category f 2 1 0 0 1 2 3 4 f 2 1 0 0 1 2 3 4 Cups of Coffee Cups of Coffee Frequency DistribuNon Graph 4 3 Frequency DistribuNon Graph 4 3 2. Draw in bars with height equal to frequency for each category f 2 1 0 0 1 2 3 4 f 2 1 0 0 1 2 3 4 Cups of Coffee Cups of Coffee 32 4/4/11 Frequency DistribuNon Graph 4 3 4 3 Frequency DistribuNon Graph f 2 1 0 0 1 2 3 4 f 2 1 Ryan 0 0 1 2 3 4 Cups of Coffee Cups of Coffee Frequency DistribuNon Graph 4 3 4 3 Frequency DistribuNon Polygon f 2 f Jon Ryan 2 1 0 1 0 0 1 2 3 4 0 1 2 3 4 Cups of Coffee Cups of Coffee 33 4/4/11 Frequency DistribuNon Polygon 4 . 0 Frequency DistribuNon Table . 3 0 p . 2 0 . 1 0 0 0 1 2 3 4 Types of Frequency DistribuNons Frequency DistribuNon Graph Grouped Frequency DistribuNon Table Grouped Frequency DistribuNon Graph Cups of Coffee Popula7on of ci7es in thousands N = 100 ci7es Frequency DistribuNon Table Types of Frequency DistribuNons Frequency DistribuNon Graph Grouped Frequency DistribuNon Table Grouped Frequency DistribuNon Graph 220, 430, 301, 40, 290, 3000, 1230, 647, 356, 910, 22, 37, 483, 273, 84, 912, 378, 374, 12, 0.4, 2, 121, 54, 72, 145, 8, 376, 5, 981, 43, 777, 35, 427, 35, 467, 19, 23, 456, 37, 45, 366, 298... 34 4/4/11 Grouped Frequency DistribuNon Table Pop. f Grouped Frequency DistribuNon Table Pop. Intervals rather than values f Grouped Frequency DistribuNon Table Pop. f Class Intervals 1. Table should have about 10 intervals 2. Class interval width should be simple number 3. Bogom score in each class interval should be a mulNple of width 4. All intervals should be the same width Frequency of values in interval rather than frequency of specific values 35 4/4/11 Class Intervals 1. Table should have about 10 intervals 2. Class interval width should be simple number 3. Bogom score in each class interval should be a mulNple of width 4. All intervals should be the same width Grouped Frequency DistribuNon Table Pop. f ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ Choose intervals Determining Intervals 1. Find range 4100 0.4 = 4099.6 2. Split into ~10 interval 4099.6/10 = 409.96 per interval... Grouped Frequency DistribuNon Table Pop. f 3. Balance rules 1 and 2 Width of 400 means 11 intervals will contain all values 36 4/4/11 Grouped Frequency DistribuNon Table Pop. f 4000-4399 3600-3999 3200-3599 2800-3199 2400-2799 2000-2399 1600-1999 1200-1599 800-1199 400-799 0 - 399 Grouped Frequency DistribuNon Table Pop. f 4000-4399 3600-3999 3200-3599 2800-3199 2400-2799 2000-2399 1600-1999 1200-1599 800-1199 400-799 0 - 399 Enter frequencies Grouped Frequency DistribuNon Table Pop. f 4000-4399 3600-3999 3200-3599 2800-3199 2400-2799 2000-2399 1600-1999 1200-1599 800-1199 400-799 0 - 399 1 0 1 0 0 2 6 16 41 19 14 Enter frequencies Grouped Frequency DistribuNon Table Pop. f 4000-4399 3600-3999 3200-3599 2800-3199 2400-2799 2000-2399 1600-1999 1200-1599 800-1199 400-799 0 - 399 1 0 1 0 0 2 6 16 41 19 14 37 4/4/11 Frequency DistribuNon Table Frequency DistribuNon Table Types of Frequency DistribuNons Frequency DistribuNon Graph Grouped Frequency DistribuNon Table Grouped Frequency DistribuNon Graph Types of Frequency DistribuNons Frequency DistribuNon Graph Grouped Frequency DistribuNon Table Grouped Frequency DistribuNon Graph Grouped Frequency DistribuNon Graph 45 40 35 30 25 20 15 10 5 0 45 40 35 30 25 20 15 10 5 0 Grouped Frequency DistribuNon Graph f f PopulaNon of City (thousands) 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 PopulaNon of City (thousands) 38 f 45 40 35 30 25 20 15 10 5 0 45 40 35 30 25 20 15 10 5 0 f Grouped Frequency DistribuNon Graph Grouped Frequency DistribuNon Graph PopulaNon of City (thousands) PopulaNon of City (thousands) 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 f 45 40 35 30 25 20 15 10 5 0 f 45 40 35 30 25 20 15 10 5 0 Grouped Frequency DistribuNon Graph Grouped Frequency DistribuNon Graph PopulaNon of City (thousands) PopulaNon of City (thousands) 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 4/4/11 39 f 45 40 35 30 25 20 15 10 5 0 45 40 35 30 25 20 15 10 5 0 f Grouped Frequency DistribuNon Graph Grouped Frequency DistribuNon Graph PopulaNon of City (thousands) PopulaNon of City (thousands) 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 f 45 40 35 30 25 20 15 10 5 0 f 45 40 35 30 25 20 15 10 5 0 Grouped Frequency DistribuNon Graph Grouped Frequency DistribuNon Graph PopulaNon of City (thousands) PopulaNon of City (thousands) 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 4/4/11 40 f 45 40 35 30 25 20 15 10 5 0 45 40 35 30 25 20 15 10 5 0 f Grouped Frequency DistribuNon Graph Grouped Frequency DistribuNon Graph PopulaNon of City (thousands) PopulaNon of City (thousands) 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 f 45 40 35 30 25 20 15 10 5 0 f 45 40 35 30 25 20 15 10 5 0 Grouped Frequency DistribuNon Graph Grouped Frequency DistribuNon Graph PopulaNon of City (thousands) PopulaNon of City (thousands) 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 4/4/11 41 f 45 40 35 30 25 20 15 10 5 0 p 45 . 40 . 35 . . 30 . 25 . 20 15 . . 10 .05 0 PopulaNon of City (thousands) Grouped Frequency DistribuNon Graph Grouped Frequency DistribuNon Polygon PopulaNon of City (thousands) PopulaNon of City (thousands) 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 0 - 3 40 99 0- 80 799 0- 12 119 00 9 - 16 159 00 9 - 20 199 00 9 - 24 239 00 9 - 28 279 00 9 - 32 319 00 9 - 36 359 00 9 - 40 399 00 9 -4 39 9 Grouped Frequency DistribuNon Graph f 45 40 35 30 25 20 15 10 5 0 4/4/11 42 4/4/11 For Next Time Read: Chapter 3 Central Tendency Variability Start/Skim Chapter 4 43 ...
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