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# Stats 240 Chapters 1-5 Study Guide JUST 240_04

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This 6 page Study Guide was uploaded by Vanessa Olivo on Friday October 7, 2016. The Study Guide belongs to JUST 240_04 at Montclair State University taught by Venezia Michalsen in Fall 2016. Since its upload, it has received 29 views. For similar materials see Statistics for Social Research in Justice Studies at Montclair State University.

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Date Created: 10/07/16

Study Guide Statistics 240 Chapter 1 places or objects in the sample as a way to make a statement that will generalize to thee, population Sampling Techniques • Non probability Biased Not ever element has an equal & known factor of being selected Not random No list Ex: snowball sampling (refer a friend), availability sampling (right in front of you), judgment sampling (who they think would be appropriate for the sample) and quota sampling (over sample characteristics) • Probability Random Selection Every element has an equal & known factor of being selected True random sampling includes replacement Yes generalize from sample to population Non biased List Ex: simple random sampling (plain, random), systematic random sampling (select every 10 name from address book), stratified random sampling (go by floors then within floors go to classrooms and within classrooms, you would pick students), waited random sampling (over represent something) Population: the universe of people, objects, or locations in which researchers wish to study Chapter 2 Independent Variable • A factor or characteristic that is being used in a sample to try to explain or predict a dependent variable Dependent Variable • The phenomenon that researchers plan to study, explain, or predict Examples: What are the independent and dependent variables? 1. A researcher wishes to test the hypothesis that low education affects crime. She gathers a sample of people aged 25 or older. 2. A researcher wishes to test the hypothesis that arrest deters recidivism. She gathers a sample of people who have been arrested. 3. A researcher wishes to test the hypothesis that poverty affects violent crime. He gathers a sample of neighborhoods. 4. A researcher believes smoking causes attitude problems in American adolescent boys, and decides to do a study to investigate this. 5. A researcher wishes to test the hypothesis that prison architectural design affects the number of inmate-on-inmate assaults that take place inside a facility. He gathers a sample of prisons. Levels of Measurement • Nominal (Nome/Name) Pets Gender Race Cannot be ranked, no zero • Ordinal Class rank Chain of command Low class, Middle class, High class Can be ranked, no zero • Ratio (continuous) Age Money # or $ is ratio True zero Examples: Identify the level of measurement of each of the following variables: 1. Suspects race measures as white, black, latino, and other The level of measurement is nominal because races cannot be ranked. One is not higher than the other. 2. The sentence received by convicted defendants, measured as jail, prison, probation, fine and other The level of measurement is nominal because it can’t be ranked. 3. The total number of status offenses that adult offenders reported having committed as juveniles The level of measurement is ratio because it contains true zero. 4. The amount of money, in dollars, that a police department collects annually from drug asset forfeitures The level of measurement is ratio because it has numbers and it contains a true zero. 5. Prison security level measures as minimum, medium, and maximum The level of measurement is ordinal because it can be ranked. One is less than the other and one if greater than the other. 6. How many times have you taken small items from stores without paying for those items. Please write in ____ The level of measurement would be ratio because you would have to write in a number. 7. How many times have you taken small items from stores without paying for those items. Please circle the following: Never, 1-2 times, 3-4 times, 5+ times The level of measurement would be ordinal because it can be ranked. 8. How many times have you taken small items from stores without paying for those items. Please circle the following: Yes or No The level of measurement would be nominal because the options yes or no cannot be ranked. Chapter 3 ▯▯▯▯▯▯▯▯▯ Formula of Proportion= ▯ (▯▯▯▯▯ ▯▯▯▯▯▯ ▯▯▯▯) Proportion is a form of frequency that ranges from 0.00 to 1.00 Formula of Percentage= proportion x 100 Percentages is a form of frequency that ranges from 0.00 to 100.00 Cumulative A frequency, proportion, or percentage obtained by adding a given number to all numbers below it Examples: Mostseriousarrestcharge f cf p cp pct cpct Violentoffense 13,938 13,938 .025(13,938/55,903) 0.25(13,938/55,903) 24.93(13,938/55,903x100) 24.93 Propertyoffense 16,241 30,179(add13,938+16,241) .29(16,241/55,903) .54(30,179/55,903) 29.05(16,241/55,903x100) 53.98 DrugOffense 18,220 48,399(add30,179+18,220) .33(18,220/55,903) .87(48,399/55,903) 32.59(18,220/55,903x100) 86.57 Public-OrderOffense 7,504 55,903(add48,399+7,504) .13(7,504/55,903) 1.00(55,903/55,903) 13.42(7,504/55,903x100) 99.99 N= 55,903 1.00(totalof^) 99.99(totalof^) X(Variable) Frequency Proportion Cumulative % Cumulative% Proportion Democratic 8 0.36(8/22) 0.36 36 36 Republican 11 0.5(11/22) 0.86(add0.05) 5 86 Independent 1 0.05(1/22) 0.91(add0) 5 91 Libertarian 0 0(0/22) 0.91(add0) 0 91 Green 0 0(0/22) 0.91(add0.09) 0 91 Undecided 2 0.09(2/22) 1.00 9 100 Nominal and Ordinal Level of Measurement Pie chart v Have relatively few classes v 5 classes or less Bar chart v Accommodate variables with many classes v 6 or more classes Ratio Level of Measurement Histograms v Bar touches one another Line graph Chapter 4 Measures of Central Tendency • Mode Value that occurs the most frequently Nominal, Ordinal, Ratio • Median Cuts the distribution in half- 50%-50% MP= (▯▯▯) ▯ N=same size (ratio), add the frequencies (ordinal) If N is even then find the two middle numbers, add them together and divide by 2 Vary effective by OUTLIERS (numbers that aren’t around the same numbers as others) Ordinal and Ratio • Mean Arithmetic average of a data set ???? = ▯ ▯ Ratio Chapter 5 • Variation Ratio (0.00 to 1.00) Calculate the proportion of the cases located outside the modal category ▯▯▯▯▯ VR=1.00 − ▯ Nominal and Ordinal Example: Security Level f Minimum 969 Medium 480 Maximum 350 Super Maximum 22 N= 1,821 Level of measurement: Ordinal (it can be ranked) Mode- Minimum; the frequency of the mode is 969 Median- 22, 350, 480, 969 (1,821+1)/2= 1822/2=911 Variation Ratio: 1.00- (969/1821)= 1.00-0.53=0.47 Range: 22 to 969 or 947 • Quartiles Divides distribution in quarters: 25 (top 25%), 50 (median), 75 (lower 25%) Interval • Range Calculated by subtracting the smallest score from the largest Three ways to calculate range: o 19 to 27 o 27-19=8 o 27.5-18.5=9 • Variance A measure of dispersion calculated as the mean of the squared deviation scores Ratio Population variance equation is: Sample variance equation is: 1 :findthemean nd v 2 :subtracttherawscorefromthemeantoproducepositiveornegativedeviationscores rd o 3 :inordertogetridofthenegativedeviationscore,wemustsquareallthescores § 4 :addallthescorestogetheraftersquaringeachandthendividethesumby N(samplesize)-1 • StandardDeviation Thesquarerootofthevariance Populationstandarddeviationequationis: Samplestandarddeviationequationis: Examples: Region Assaultsper100officers Northeast 8.20 Midwest 9.90 South 10.20 West 11.60 N=4 Level of Measurement: Ratio (numbers) Mode- 11.60 Median- 8.20, 9.90,10.20, 11.60 (N+1/2) = 5/2=2.5 then 9.90+10.20=20.1/2=10.05 Mean- 8.20 + 9.90 + 10.20 + 11.60= 39.9/4= 9.98 The most appropriate measure of central tendency would be the MEAN because Variance- 8.20-9.98= (-1.78)^2=3.168. 9.90-9.98= (-0.08)^2=0.006 10.20-9.98= (0.22)^2=0.048 11.60-9.98= (1.62)^2=2.624 Add the square values= 5.846/(n-1)= 5.846/3=1.949 s = 1.949 s= 1.396 State Inmates Indiana 12 Kansas 9 Missouri 47 Nebraska 11 Ohio 139 South Dakota 3 N=6 Level of Measurement: Ratio (# of inmates) Mode- Ohio Mean- 221/6=36.83, 47,139; 11+12=23/2=11.5 The most appropriate measure of central tendency would be MEDIAN because the data contains two outliers, 47 and 139. Variance-12-36.83= (-24.83)^2=616.53 9-36.83= (-27.83)^2=774.51 47-36.83= (10.17)^2=103.43 11-36.83= (-25.83)^2=667.19 139-36.83=(102.17)^2=10,438 3-36.83= (-33.83)^2=1144.47 2dd the square values=13,774.13/(n-1)= 13,774.13/5=2748.83 s = 2748.83 s= 52.43 SPSS Paste instead of OK Graphà legacy dialogs

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