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Crimes by State XXXXXXXXXX Bureau of Justice Statistics Filename: p17t04.csv Table 4. Sentenced prisoners under the jurisdiction of state or federal correctional authorities, by sex, 2016 and...

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Crimes by State XXXXXXXXXX
    Bureau of Justice Statistics
    Filename: p17t04.csv
    Table 4. Sentenced prisoners under the jurisdiction of state or federal co
ectional authorities, by sex, 2016 and 2017
    Report title: Prisoners in 2017 NCJ 252156
    Data source: Bureau of Justice Statistics, National Prisoner Statistics, 2016 and 2017.
    Authors: Jennifer Bronson, Ph.D., and E. Ann Carson, Ph.D., BJS Statisticians
    Refer questions to: XXXXXXXXXX or XXXXXXXXXX
    Date of version: 4/25/2019
    Table 4. Sentenced prisoners under the jurisdiction of state or federal co
ectional authorities, by sex, 2016 and 2017
            2016                2017                Percent change, 2016–2017
    Jurisdiction        Total    Male    Female        Total    Male    Female        Total        Male        Female        Hypothesis Test
        Alabama    27,799    25,593    2,206        23,724    21,968    1,756        -14.7        -14.2        -20.4    %    Sample Mean
        Alaska/c    2,089    1,982    107        1,905    1,828    77        -8.8        -7.8        -28    %    Tail Type
        Arizona    40,849    37,131    3,718        40,263    36,543    3,720        -1.4        -1.6        0.1    %    Null Hypothesis
        Arkansas    17,476    16,111    1,365        18,028    16,617    1,411        3.2        3.1        3.4        Alt Hypothesis
        California/d    129,080    123,261    5,819        129,920    124,127    5,793        0.7        0.7        -0.4        Standard Score
        Colorado    19,862    17,963    1,899        19,824    17,925    1,899        -0.2        -0.2        0        P-Value
        Connecticut/c    10,365    9,804    561        9,626    9,142    484        -7.1        -6.8        -13.7        Conclusion?
        Delaware/c    4,090    3,889    201        4,066    3,882    184        -0.6        -0.2        -8.5
        Florida    99,974    93,111    6,863        98,504    91,779    6,725        -1.5        -1.4        -2        Confidence Interval
        Georgia    53,064    49,324    3,740        53,094    49,315    3,779        0.1        0        1        z(α/2)
        Hawaii/c    3,629    3,271    358        3,425    3,154    271        -5.6        -3.6        -24.3        EBM
        Idaho    7,376    6,416    960        7,752    6,761    991        5.1        5.4        3.2        Lower Limit
        Illinois    43,657    41,044    2,613        41,427    39,148    2,279        -5.1        -4.6        -12.8        Upper Limit
        Indiana    25,530    23,325    2,205        26,001    23,587    2,414        1.8        1.1        9.5
        Iowa    8,998    8,181    817        8,999    8,197    802        0        0.2        -1.8
        Kansas    9,628    8,831    797        9,687    8,846    841        0.6        0.2        5.5
        Kentucky    23,018    20,077    2,941        23,539    20,518    3,021        2.3        2.2        2.7
        Louisiana    35,646    33,665    1,981        33,706    31,749    1,957        -5.4        -5.7        -1.2
        Maine    1,828    1,675    153        1,795    1,643    152        -1.8        -1.9        -0.7
        Maryland    19,821    19,010    811        19,232    18,399    833        -3        -3.2        2.7
        Massachusetts    8,494    8,140    354        8,286    7,976    310        -2.4        -2        -12.4
        Michigan    41,122    38,880    2,242        39,666    37,515    2,151        -3.5        -3.5        -4.1
        Minnesota    10,592    9,818    774        10,708    9,974    734        1.1        1.6        -5.2
        Mississippi    18,666    17,397    1,269        18,471    17,184    1,287        -1        -1.2        1.4
        Missouri    32,461    29,124    3,337        32,592    29,197    3,395        0.4        0.3        1.7
        Montana    3,814    3,405    409        3,698    3,282    416        -3        -3.6        1.7
        Ne
aska    5,235    4,825    410        5,257    4,837    420        0.4        0.2        2.4
        Nevada    13,637    12,403    1,234        13,671    12,405    1,266        0.2        0        2.6
        New Hampshire    2,818    2,591    227        2,750    2,524    226        -2.4        -2.6        -0.4
        New Jersey    19,786    18,952    834        19,585    18,811    774        -1        -0.7        -7.2
        New Mexico/e    6,972    6,276    696        7,189    6,422    767        -3.1        -2.3        -10.2
        New York    50,620    48,356    2,264        49,360    47,103    2,257        -2.5        -2.6        -0.3
        North Carolina    34,596    32,085    2,511        35,283    32,649    2,634        2        1.8        4.9
        North Dakota/e,f    1,779    1,568    211        1,711    1,514    197        3.8        3.4        6.6
        Ohio    52,175    47,581    4,594        51,478    47,052    4,426        -1.3        -1.1        -3.7
        Oklahoma/d    29,531    26,145    3,386        27,729    24,615    3,114        -6.1        -5.9        -8
        Oregon/d    15,150    13,846    1,304        15,200    13,877    1,323        0.3        0.2        1.5
        Pennsylvania    49,000    46,188    2,812        48,074    45,281    2,793        -1.9        -2        -0.7
        Rhode Island/c    2,030    1,962    68        1,808    1,739    69        -10.9        -11.4        1.5
        South Carolina    20,371    18,981    1,390        19,541    18,233    1,308        -4.1        -3.9        -5.9
        South Dakota    3,820    3,323    497        3,959    3,424    535        3.6        3        7.6
        Tennessee    28,203    25,481    2,722        28,980    25,969    3,011        2.8        1.9        10.6
        Texas    157,903    144,928    12,975        157,584    144,750    12,834        -0.2        -0.1        -1.1
        Utah/d    6,171    5,765    406        6,437    5,945    492        4.3        3.1        21.2
        Vermont/c    1,229    1,146    83        1,126    1,021    105        -8.4        -10.9        26.5
        Virginia    37,813    34,704    3,109        37,158    34,004    3,154        -1.7        -2        1.4
        Washington    19,019    17,377    1,642        19,540    17,811    1,729        2.7        2.5        5.3
        West Virginia    7,162    6,286    876        7,092    6,274    818        -1        -0.2        -6.6
        Wisconsin    22,144    20,734    1,410        22,682    21,147    1,535        2.4        2        8.9
        Wyoming    2,374    2,088    286        2,473    2,181    292        4.2        4.5        2.1
    Note: Jurisdiction refers to the legal authority of state or federal co
ectional officials over a prisoner, regardless of where the prisoner is held. Counts are for December 31 of each year and are based on prisoners with a sentence of more than one year.
    :Not calculated.
    a/Includes prisoners held in non-secure, privately operated community co
ections facilities and juveniles held in contract facilities.
    
Total and state estimates for 2016 include imputed counts for North Dakota, which did not submit 2016 National Prisoner Statistics (NPS) data. Total and state estimates for 2017 include imputed counts for New Mexico and North Dakota, which did not submit 2017 NPS data. See Methodology.
    c/Prisons and jails form one integrated system. Data include total jail and prison populations.
    d/State submitted updated 2016 sentenced population counts.
    e/State did not submit 2017 NPS data. Counts were imputed for 2017 and should not be compared to 2016 counts. See Methodology.
    f/State did not submit 2016 NPS data. Counts were imputed for 2016 and should not be compared to 2017 counts. See Methodology.
    Source: Bureau of Justice Statistics, National Prisoner Statistics, 2016 and 2017.
Gender Perception in Workforce
    Occupation    bls_proportion_women    image_search_proportion_women    Difference        Hypothesis Test
    singer    0.377    0.617    -0.24        Sample Proportion
    mechanic    0.024    0.242    -0.218        Tail Type
    aircraft pilot    0.062    0.271    -0.209        Null Hypothesis
    maintenance worker    0.045    0.226    -0.181        Alt Hypothesis
    computer support specialist    0.271    0.442    -0.171        Standard Score
    electrical engineer    0.123    0.271    -0.148        P-Value
    chemical engineer    0.169    0.31    -0.141        Conclusion?
    judge    0.281    0.415    -0.134
    railroad conductor    0.052    0.179    -0.127
    computer programmer    0.212    0.338    -0.126
    chemical technician    0.274    0.395    -0.121
    electrician    0.025    0.129    -0.104
    police    0.136    0.237    -0.101
    paramedic    0.306    0.4    -0.094
    model    0.784    0.875    -0.091
    clergy    0.17    0.258    -0.088
    truck driver    0.062    0.148    -0.086
    construction manager    0.074    0.153    -0.079
    physician    0.4    0.478    -0.078
    radio operator    0.144    0.216    -0.072
    plumber    0.022    0.091    -0.069
    emergency medical technician    0.306    0.373    -0.067
    cook    0.393    0.456    -0.063
    retail buyer    0.558    0.62    -0.062
    machinist    0.05    0.111    -0.061
    dispatcher    0.574    0.634    -0.06
    mechanical engineer    0.092    0.152    -0.06
    distribution manager    0.192    0.25    -0.058
    shipping clerk    0.313    0.368    -0.055
    construction inspector    0.102    0.155    -0.053
    laborer    0.199    0.25    -0.051
    chemist    0.383    0.433    -0.05
    mail clerk    0.368    0.418    -0.05
    magistrate    0.281    0.33    -0.049
    flight attendant    0.729    0.774    -0.045
    concierge    0.311    0.345    -0.034
    building inspector    0.102    0.132    -0.03
    chef    0.197    0.225    -0.028
    farmer    0.252    0.28    -0.028
    network administrator    0.235    0.259    -0.024
    athlete    0.364    0.379    -0.015
    head cook    0.197    0.211    -0.014
    stock clerk    0.379    0.382    -0.003
    computer systems analyst    0.389    0.391    -0.002
    pharmacist    0.575    0.575    0
    lifeguard    0.496    0.492    0.004
    customer service representative    0.651    0.641    0.01
    veterinarian    0.625    0.613    0.012
    artist    0.519    0.507    0.012
    industrial engineer    0.226    0.184    0.042
    engineering technician    0.2    0.147    0.053
    inspector    0.379    0.324    0.055
    property manager    0.486    0.43    0.056
    co
ectional officer    0.285    0.229    0.056
    real estate sales agent    0.571    0.509    0.062
    li
ary assistant    0.801    0.737    0.064
    food service manager    0.463    0.398    0.065
    archivist    0.614    0.548    0.066
    bellhops    0.311    0.241    0.07
    butcher    0.243    0.167    0.076
    film director    0.298    0.221    0.077
    musician    0.377    0.293    0.084
    security guard    0.243    0.151    0.092
    dietitian    0.941    0.846    0.095
    restaurant hostess    0.859    0.759    0.1
    receptionist    0.91    0.808    0.102
    bailiff    0.285    0.181    0.104
    jailer    0.285    0.179    0.106
    real estate manager    0.486    0.376    0.11
    announcer    0.231    0.119    0.112
    cashier    0.727    0.607    0.12
    reporter    0.553    0.43    0.123
    janitor    0.352    0.229    0.123
    marketing specialist    0.608    0.478    0.13
    municipal clerk    0.752    0.617    0.135
    li
arian    0.795    0.655    0.14
    bus driver    0.478    0.336    0.142
    physician assistant    0.709    0.564    0.145
    telemarketer    0.694    0.547    0.147
    nutritionist    0.941    0.79    0.151
    veterinary assistant    0.842    0.691    0.151
    medical scientist    0.521    0.366    0.155
    chief executive    0.28    0.102    0.178
    travel agent    0.827    0.639    0.188
    general manager    0.341    0.151    0.19
    secretary    0.95    0.743    0.207
    probation officer    0.635    0.427    0.208
    co
espondent    0.553    0.342    0.211
    legal assistant    0.863    0.643    0.22
    health information technician    0.917    0.696    0.221
    licensed practical nurse    0.895    0.667    0.228
    clinical laboratory technician    0.693    0.458    0.235
    administrative assistant    0.95    0.708    0.242
    tax collector    0.584    0.319    0.265
    file clerk    0.814    0.547    0.267
    paralegal    0.863    0.589    0.274
    nurse practitioner    0.922    0.64    0.282
    bartender    0.573    0.286    0.287
    office clerk    0.831    0.539    0.292
    restaurant host    0.859    0.546    0.313
    news analyst    0.553    0.234    0.319
    claims adjuster    0.617    0.284    0.333
    medical records technician    0.917    0.568    0.349
    interviewer    0.85    0.5    0.35
    bill collector    0.713    0.195    0.518
ls_proportion_women: the true proportion of women who work in an occupation
image_search_proportion_women: the proportion of women who appeared in image searches for each occupation.
Survey Key
    original    short
    I enjoy listening to music.    Music
    I prefer.    Slow songs or fast songs
    Dance, Disco, Funk    Dance
    Folk music    Folk
    Country    Country
    Classical    Classical music
    Musicals    Musical
    Pop    Pop
    Rock    Rock
    Metal, Hard rock    Metal or Hardrock
    Punk    Punk
    Hip hop, Rap    Hiphop, Rap
    Reggae, Ska    Reggae, Ska
    Swing, Jazz    Swing, Jazz
    Rock n Roll    Rock n roll
    Alternative music    Alternative
    Latin    Latino
    Techno, Trance    Techno, Trance
    Opera    Opera
    I really enjoy watching movies.    Movies
    Ho
or movies    Ho
o
    Thriller movies    Thrille
    Comedies    Comedy
    Romantic movies    Romantic
    Sci-fi movies    Sci-fi
    War movies    Wa
    Tales    Fantasy/Fairy tales
    Cartoons    Animated
    Documentaries    Documentary
    Western movies    Western
    Action movies    Action
    History    History
    Psychology    Psychology
    Politics    Politics
    Mathematics    Mathematics
    Physics    Physics
    Internet    Internet
    PC Software, Hardware    PC
    Economy, Management    Economy Management
    Biology    Biology
    Chemistry    Chemistry
    Poetry reading    Reading
    Geography    Geography
    Foreign languages    Foreign languages
    Medicine    Medicine
    Law    Law
    Cars    Cars
    Art    Art exhibitions
    Religion    Religion
    Outdoor activities    Countryside, outdoors
    Dancing    Dancing
    Playing musical instruments    Musical instruments
    Poetry writing    Writing
    Sport and leisure activities    Passive sport
    Sport at competitive level    Active sport
    Gardening    Gardening
    Cele
ity lifestyle    Cele
ities
    Shopping    Shopping
    Science and technology    Science and technology
    Theatre    Theatre
    Socializing    Fun with friends
    Adrenaline sports    Adrenaline sports
    Pets    Pets
    Flying    Flying
    Thunder, lightning    Storm
    Darkness    Darkness
    Heights    Heights
    Spiders    Spiders
    Snakes    Snakes
    Rats, mice    Rats
    Ageing    Ageing
    Dangerous dogs    Dangerous dogs
    Public speaking    Fear of public speaking
    Smoking habits    Smoking
    Drinking    Alcohol
    I live a very healthy lifestyle.    Healthy eating
    I take notice of what goes on around me.    Daily events
    I try to do tasks as soon as possible and not leave them until last minute.    Prioritising workload
    I always make a list so I don't forget anything.    Writing notes
    I often study or work even in my spare time.    Workaholism
    I look at things from all different angles before I go ahead.    Thinking ahead
    I believe that bad people will suffer one day and good people will be rewarded.    Final judgement
    I am reliable at work and always complete all tasks given to me.    Reliability
    I always keep my promises.    Keeping promises
    I can fall for someone very quickly and then completely lose interest.    Loss of interest
    I would rather have lots of friends than lots of money.    Friends versus money
    I always try to be the funniest one.    Funniness
    I can be two faced sometimes.    Fake
    I damaged things in the past when angry.    Criminal damage
    I take my time to make decisions.    Decision making
    I always try to vote in elections.    Elections
    I often think about and regret the decisions I make.    Self-criticism
    I can tell if people listen to me or not when I talk to them.    Judgment calls
    I am a hypochondriac.    Hypochondria
    I am emphatetic person.    Empathy
    I eat because I have to. I don't enjoy food and eat as fast as I can.    Eating to survive
    I try to give as much as I can to other people at Christmas.    Giving
    I don't like seeing animals suffering.    Compassion to animals
    I look after things I have bo
owed from others.    Bo
owed stuff
    I feel lonely in life.    Loneliness
    I used to cheat at school.    Cheating in school
    I wo
y about my health.    Health
    I wish I could change the past because of the things I have done.    Changing the past
    I believe in God.    God
    I always have good dreams.    Dreams
    I always give to charity.    Charity
    I have lots of friends.    Number of friends
    Timekeeping.    Punctuality
    Do you lie to others?    Lying
    I am very patient.    Waiting
    I can quickly adapt to a new environment.    New environment
    My moods change quickly.    Mood swings
    I am well mannered and I look after my appearance.    Appearence and gestures
    I enjoy meeting new people.    Socializing
    I always let other people know about my achievements.    Achievements
    I think carefully before answering any important letters.    Responding to a serious lette
    I enjoy childrens' company.    Children
    I am not afraid to give my opinion if I feel strongly about something.    Assertiveness
    I can get angry very easily.    Getting angry
    I always make sure I connect with the right people.    Knowing the right people
    I have to be well prepared before public speaking.    Public speaking
    I will find a fault in myself if people don't like me.    Unpopularity
    I cry when I feel down or things don't go the right way.    Life struggles
    I am 100% happy with my life.    Happiness in life
    I am always full of life and energy.    Energy levels
    I prefer big dangerous dogs
Answered 7 days After Nov 13, 2022

Solution

Shikha answered on Nov 20 2022
35 Votes
Milestone 3: Inference
Overview and Objectives
The primary objective of this project will be to perform a few hypothesis tests, make inferences on the test statistics, and state null/alternative hypotheses. The techniques used in modern inferential research require software beyond our cu
ent means (SPSS, R, SAS); however, we are nonetheless able to observe a few examples that are illustrative of the research process.
You will work with populations, samples, and proportions in these exercises. You’ll then determine whether to use a Z-statistic or T-statistic to determine whether to reject the null hypothesis and you’ll also make connections between hypothesis testing and confidence intervals. You’ll have the opportunity to explore real-world datasets in the fields of criminal justice, equity, and surveying.
With a firm knowledge of this statistical concept, you’ll possess the conceptual knowledge necessary to further pursue these techniques if they are of interest to you.
Part One: Crime Analysis from 2016-2017
National law enforcement noticed an overall decline in crimes among US Citizens. This data set records the number of crimes in each state and the percent change from 2016 to 2017. Let’s suppose that leadership would like to conduct a hypothesis test at the 99% significance level that crime has decreased over time (by using percent change). For this part, you should look at the total percent change column to run your test.
Performing the Test
Step 1:Write the null hypothesis/alternative hypotheses below. Determine the tail type.
:     left tail test
Step 2:Perform the Hypothesis Test in Excel. Fill out the cells indicated on the spreadsheet and determine whether to accept
eject the null hypothesis.
Ans : Filled in sheet
Step 3:Find a 99% confidence interval for the percent change from 2016 to 2017 by filling out the cells in the Excel sheet.
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