Lab012021A - Bus wating time(in minutes) was measured in a...

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Unformatted text preview: Bus wating time(in minutes) was measured in a bus stop during 1 hour. (a) What is the appropriate graph for this kind of data set? Why? a) This is a numerical data set therefore histogram, frequency polygon and ogive are appropriate. (b) How many observations do you have? There are 50 observations. Some ways to find this out - highlight data array area and find the count on lower right of Using data-data analysis-histogram, or using count( ) function. You can also develop your own way to check this. (c) Using the data set, create a histogram with classes of 0~5, 5~10, 10~15, 15~20, 20~25, 25~30, 30~35 (d) How do you deal with the upper limit such as 5 for class 0~5? Since Excel treats upper limits as if they were closed, we need to set the upper limit slightly less than the actual. For e) Using the first set of classes, draw a frequency polygon and ogive for the data. Do these graphs convey some add A frequency polygon is a different expression of a histogram using line. It contains similar information with a histogram, though a frequency polygon makes it easier to observe a trend. Ogive gives you the information about cumulative distribution of observations. Wating time 6 5 33 6 17 6 18 6 27 1 14 7 11 8 22 1 7 4 15 19 20 17 14 12 class 0~5 5~10 10~15 15~20 20~25 25~30 30~35 bin range 4.99 9.99 14.99 19.99 24.99 29.99 34.99 bin range Frequency 0~5 12 5~10 16 10~15 11 15~20 7 20~25 2 25~30 1 30~35 1 20 15 10 Frequency 5 0 0~5 bin range Frequency 0 0 2.5 12 7.5 16 12.5 11 17.5 7 22.5 2 Fre 20 15 10 Frequency 5 0 0 2.5 15 10 Frequency 5 0 0 2.5 7 6 4 3 8 14 1 9 2 17 14 3 2 9 19 2 10 3 11 14 6 7 12 7 3 11 27.5 32.5 37.5 1 1 0 bin range Frequency Cumulative % 0 0 0 5 12 24.00% 10 16 56.00% 15 11 78.00% 20 7 92.00% 25 2 96.00% 30 1 98.00% 35 1 100.00% e count on lower right of the screen, wn way to check this. 25~30, 30~35 less than the actual. For example, 4.99 instead of 5. graphs convey some additional information? to observe a trend. Histogram 20 15 10 Frequency 5 0 0~5 5~10 15~20 25~30 10~15 20~25 30~35 Waiting time Column H Frequency Polygon 20 15 10 Frequency 5 0 0 2.5 7.5 12.5 22.5 32.5 17.5 27.5 37.5 bin range Column H 15 10 Frequency 5 0 0 2.5 7.5 12.5 22.5 32.5 17.5 27.5 37.5 bin range Column H Ogive 1.2 1 0.8 Frequency 0.6 0.4 0.2 0 0 5 10 15 20 25 30 35 bin range Column I These activities will be performed basically based on our lab manual, only using different set of data. Numbers below are weight measurements of Indiana Hoosiers football team roster. (from IU atheletics webpa (a) How many observations do you have? There are 110 observations. Some ways to find this out - select data array area and find the count on lower right of th Using data-data analysis-histogram, or using count( ) function. You can also develop your own way to check this. (b) Is this data numerical? If so, is it continuous or discrete? Weight is numerical, continuous data. Its value contains meaningful information itself. (c) Draw two histogram based on this data, one with the bin class size of 20 lbs and the other with the bin class size (d) Which histogram is more informative? Why? The first histgram carries more detailed information about team weights, as the bimodal characteristic of the distribution no longer appears with the second one. (lbs) 204 class bin range bin range Frequency 187 160~180 179.99 160~180 4 271 180~200 199.99 180~200 22 175 200~220 219.99 200~220 26 196 220~240 239.99 220~240 18 224 240~260 259.99 240~260 8 214 260~280 279.99 260~280 6 306 280~300 299.99 280~300 14 210 300~320 319.99 300~320 10 235 320~340 339.99 320~340 2 Frequency 331 241 231 180 180 220 224 298 304 235 207 223 class bin range bin range Frequency 197 150~200 199.99 150~200 26 203 200~250 249.99 200~250 50 218 250~300 299.99 250~300 22 213 300~350 349.99 300~350 12 304 192 30 25 20 15 10 5 0 180~20 160~180 20 60 50 40 30 20 10 Frequency 50 40 247 199 199 202 188 200 160 320 290 216 185 224 198 195 296 211 249 207 263 226 218 259 181 250 198 181 195 225 206 286 294 247 285 237 209 309 231 282 299 308 284 181 314 311 237 Frequency 30 20 10 0 150 205 286 186 173 175 219 220 292 244 303 282 236 271 226 318 237 293 218 217 218 295 301 185 216 195 220 269 265 183 208 260 184 219 200 210 200 247 nt set of data. er. (from IU atheletics webpage) d the count on lower right of the screen, our own way to check this. e other with the bin class size of 50lbs. Histogram 30 25 20 15 Frequency 10 5 0 180~200 220~240 260~280 300~320 160~180 200~220 240~260 280~300 320~340 bin range Column G Histogram 60 50 40 Frequency 30 20 10 Column H 50 40 Frequency 30 20 10 0 150~200 200~250 250~300 300~350 bin range Column H A survey asks students to identify which cell phone brand they have purchased. The responses are 1. Sam Sung 2. LG 3. Nokia 4. Motorolla 5. Other a) Draw all appropriate graphs for this variable. How is this data different from the data in previous case? What is the different properties of this data set compare to the previous one? b) What do the charts tell you about the brands of cell phones used by the students? Response 1 3 1 4 3 3 3 2 1 2 1 3 2 3 3 2 3 2 3 1 3 2 2 1 4 3 2 4 5 4 2 3 2 2 a) This is a catagorical data, nominal type. Unlike the previous, the numbers do not carry any Response Frequency Sam Sung 8 LG 16 Nokia 19 Motorolla 5 Other 2 Column Chart 20 18 16 14 12 10 8 6 4 2 0 Sam Sung LG Nokia Motorolla Other Response Frequency Nokia 19 LG 16 Sam Sung 8 Motorolla 5 Other 2 Bar Chart Other Motorolla Nokia LG Sam Sung 0 2 4 6 8 10 12 14 16 18 2 b) It clearly shows that students prefer Nokia to other brands of cell phone makers. 4 2 3 2 1 2 3 3 1 3 3 2 3 5 3 2 Suggested Questions: For what type of data are pie charts and column charts appropriate? Categorical Data Think of situations where pie chart will be more helpful than column charts? Pie charts are helpful for relative frequencies while column charts are more helpful sponses are in previous case? , the numbers do not carry any meaning. Column Chart Pie Chart Frequency Sam Su LG Nokia Motoro Other Nokia Motorolla Other Bar Chart 20 18 16 14 12 10 8 6 4 2 0 Nokia LG Pareto Diagram Frequency Frequen 6 8 10 12 14 16 18 20 Sam Sung Motorolla Other cell phone makers. appropriate? than column charts? umn charts are more helpful in displaying absolute frequencies. Sam Sung LG Nokia Motorolla Other am Frequency Other f-Lab Quiz for Chapter Two 1. Describe the difference between a Pareto diagram and a column chart. (1pt) The difference between a Pareto diagram and an usual column chart is the order in which columns are pres 2. Suppose you received qualitative data which consisted of 17 categories, but you found most observations conc Pareto diagram is the most informative if most observations are concentrated in only a few of many categor 3. When creating histograms, what is the conventional way to treat the 'upper' and 'lower' bounds of the classes? Usually, lower bound is included(closed) and upper bound is excluded(open) in the bin class. (1pt) 4. What is the trick you use with Excel to execute the convention you mentioned in #3? (1pt) Since Excel treats upper limits as if they were closed, we need to set the upper limit slightly less than the ac in which columns are presented. In Pareto diagram, columns will be arrayed in order according to their heights, the ta found most observations concentrated in 3 categories among them. Of column chart or Pareto diagram, which representation only a few of many categories. (1pt) lower' bounds of the classes? Please be specific. (1pt) the bin class. (1pt) #3? (1pt) mit slightly less than the actual, for example, 4.99 instead of 5. (1pt) rding to their heights, the tallest column being leftmost and the shortest column being r ightmost. (1pt) iagram, which representation is more informative? Why?(1pt) htmost. (1pt) ...
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