首页
网站开发
桌面应用
管理软件
微信开发
App开发
嵌入式软件
工具软件
数据采集与分析
其他
首页
>
> 详细
辅导program程序、讲解R编程设计、R程序语言调试 讲解留学生Processing|辅导Python编程
项目预算:
开发周期:
发布时间:
要求地区:
Question 1 [17 marks]
A technology company has a very intensive hiring process, where each applicant is required
to complete four different tests. These tests are designed to assess various qualities,
skills and abilities that the company is looking for in prospective employees. The
technology company has collected some data on the applicants and their test scores.
Specifically, for a random selection of 500 applicants, they have recorded the following
for each applicant: their age in years (Age), their undergraduate degree (Degree) and
their score in each of the four tests (Test1, Test2, Test3 and Test4). The data is stored
in the file AssignmentData.RData in the dataframe Q1.df.
(a) [4 marks] Use some sample statistics to describe the scores for Test 1. Specifically,
based on the definitions given in the lectures, calculate the sample coefficient of
variation, the sample median and the sample range of the scores.
(b) [4 marks] Create a boxplot and a histogram of the scores for Test 1. Make sure
to give each plot a proper descriptive title and label the x-axis of the histogram
appropriately (do not just use the default title or labels). Based on these plots,
describe the distribution of scores for Test 1. Be specific in your description, making
sure to mention any interesting and/or important aspects of the distribution.
(c) [4 marks] The company wonders whether the distribution of scores for Test 1
is different between applicants who have an undergraduate degree in Computing
and applicants who have an undergraduate degree in Engineering. Create separate
histograms of the scores for Test 1 for these two groups of applicants (i.e., one
histogram for applicants with a Computing degree and one histogram for applicants
with an Engineering degree). Make sure to give each histogram a proper descriptive
title and a label for the x-axis. Based on these histograms, describe any differences
or similarities in the distribution of scores for Test 1 between these two groups of
applicants.
(d) [2 marks] The company wonders whether the spread in scores might be similar
for all tests. Determine whether or not the spread of the scores for Test 1 and Test
3 are similar. Do not conduct a hypothesis test, but make sure to provide a clear
justification for your answer based on the data.
(e) [3 marks] Test whether the mean score for Test 1 is greater than 7. Clearly state
your hypotheses and use a significance level of α = 10%. Do not use any functions
available in R or any R package that are designed to perform hypothesis tests.
Assignment S1 2021 Page 3 of 6 STAT7055
Question 2 [14 marks]
For this question you will be required to generate some sample data in R.
(a) [2 marks] First, in a single line of code, specify the seed for the random number
generator in R by using the set.seed function with your student number (without
the “u”) as the seed argument. For example, if your student number is u1234567
then you would use the line of code set.seed(1234567). Next, in a single line of
code, create a vector consisting of 100 observations that are randomly generated
from a normal distribution with mean µ = 65 and variance σ2 = 182.25 and call
this vector x (representing the variable X). Finally, in a single line of code, create
a vector consisting of 105 observations that are randomly generated from a uniform
distribution between a = 42 and b = 92 and call this vector y (representing the
variable Y ). These three lines of code must be executed in succession with no other
lines of code in between.
For the remaining parts of this question, assume that the values of µ, σ2, a and b are all
unknown and all that you have available is the sample data you generated in part (a).
(b) [4 marks] Calculate an 84% confidence interval for the population mean of the Y
values. Interpret the confidence interval. Do not use any functions available in R
or any R package that are designed to calculate confidence intervals.
(c) [4 marks] Test whether the population proportion of X values that are greater
than 75 is less than 0.351. Clearly state your hypotheses, making sure to define
any parameters, and use a significance level of α = 5%. Do not use any functions
available in R or any R package that are designed to perform hypothesis tests.
(d) [4 marks] If the X values and Y values are treated as independent samples, test
whether the population proportion of X values that are greater than 75 is greater
than the population proportion of Y values that are greater than 88. Clearly state
your hypotheses, making sure to define any parameters, and use a significance level
of α = 10%. Do not use any functions available in R or any R package that are
designed to perform hypothesis tests.
Assignment S1 2021 Page 4 of 6 STAT7055
Question 3 [23 marks]
Some data were collected on the university entrance scores for year 12 students from
four high schools over a period of four years. For each year, a sample of year 12 students
were randomly selected from each high school and their university entrance scores were
recorded. For a given high school, the same number of year 12 students were selected each
year. However, within a given year, the number of year 12 students selected may differ
between the four high schools. The data is stored in the file AssignmentData.RData in
the dataframe Q3.df. For a given year, the university entrance scores for all students
across all four high schools are given in the column named by the year (Year2005,
Year2006, Year2007 and Year2008) and the high school (1, 2, 3, or 4) to which each
student belonged is given in the column named HighSchool.
For this question, you will be analysing the university entrance scores from
2005.
(a) [2 marks] Calculate the sample mean university entrance score for each high school.
(b) [2 marks] Calculate the sample variance of university entrance scores for each high
school.
(c) [3 marks] Test whether the population variance of university entrance scores is
the same for high school 1 and high school 2. Clearly state your hypotheses and
use a significance level of α = 5%. Do not use any functions available in R or any
R package that are designed to perform hypothesis tests.
(d) [3 marks] Test whether the population mean university entrance score for high
school 2 is greater than that for high school 1 by more than 5. Clearly state your
hypotheses and use a significance level of α = 5%. Do not use any functions
available in R or any R package that are designed to perform hypothesis tests.
You will now conduct a one-way ANOVA on the university entrance scores from 2005
with high school as the factor.
(e) [8 marks] Discuss whether or not the assumptions for a one-way ANOVA hold
for this data. You do not need to conduct any hypothesis tests, but make sure to
provide clear justifications for your answer.
(f) [2 marks] Calculate the sum of squares for treatment for the one-way ANOVA.
Do not use any functions available in R or any R package that are designed to
perform an ANOVA.
(g) [3 marks] Test whether the population mean university entrance score is the same
for all four high schools. Clearly state your hypotheses and use a significance level
of α = 5%. Do not use any functions available in R or any R package that are
designed to perform hypothesis tests or an ANOVA.
Assignment S1 2021 Page 5 of 6 STAT7055
Question 4 [16 marks]
A think tank has been developing aptitude tests which they are hoping could eventually
be used as a replacement for IQ tests. They have conducted a long-term study where
they selected a random sample of 200 people and, for each person, recorded their scores
in an age-appropriate aptitude test every five years from age 5 to age 25 (Age5, Age10,
Age15, Age20 and Age25). The data is stored in the file AssignmentData.RData in the
dataframe Q4.df. The think tank is interested in whether the score in the aptitude test
taken at age 5 could be used to predict the score in later year aptitude tests.
For this question, you will be analysing the aptitude test scores at ages 5
(Age5) and 10 (Age10).
(a) [3 marks] Create a scatter plot of the aptitude test scores at age 10 against the
aptitude test scores at age 5. Make sure to give your plot an appropriate title and
appropriate labels for the x and y axes. Describe the relationship between these
two variables.
(b) [3 marks] Test whether the correlation between the aptitude test scores at age
10 and the aptitude test scores at age 5 is greater than zero. Clearly state your
hypotheses and use a significance level of α = 5%. Do not use any functions
available in R or any R package that are designed to perform hypothesis tests.
(c) [2 marks] Fit a simple linear regression model with aptitude test scores at age
10 as the dependent variable and aptitude test scores at age 5 as the independent
variable. Write down the estimated regression model.
(d) [5 marks] Discuss whether or not the assumptions for a simple linear regression
model hold for this data, making sure to provide clear justifications for your answer.
(e) [3 marks] Test whether the intercept is less than 5. Clearly state your hypotheses
and use a significance level of α = 10%. Do not use any functions available in R
or any R package that are designed to perform hypothesis tests.
END OF ASSIGNMENT
Assignment S1 2021 Page 6 of 6 STAT7055
软件开发、广告设计客服
QQ:99515681
邮箱:99515681@qq.com
工作时间:8:00-23:00
微信:codinghelp
热点项目
更多
代做ceng0013 design of a pro...
2024-11-13
代做mech4880 refrigeration a...
2024-11-13
代做mcd1350: media studies a...
2024-11-13
代写fint b338f (autumn 2024)...
2024-11-13
代做engd3000 design of tunab...
2024-11-13
代做n1611 financial economet...
2024-11-13
代做econ 2331: economic and ...
2024-11-13
代做cs770/870 assignment 8代...
2024-11-13
代写amath 481/581 autumn qua...
2024-11-13
代做ccc8013 the process of s...
2024-11-13
代写csit040 – modern comput...
2024-11-13
代写econ 2070: introduc2on t...
2024-11-13
代写cct260, project 2 person...
2024-11-13
热点标签
mktg2509
csci 2600
38170
lng302
csse3010
phas3226
77938
arch1162
engn4536/engn6536
acx5903
comp151101
phl245
cse12
comp9312
stat3016/6016
phas0038
comp2140
6qqmb312
xjco3011
rest0005
ematm0051
5qqmn219
lubs5062m
eee8155
cege0100
eap033
artd1109
mat246
etc3430
ecmm462
mis102
inft6800
ddes9903
comp6521
comp9517
comp3331/9331
comp4337
comp6008
comp9414
bu.231.790.81
man00150m
csb352h
math1041
eengm4100
isys1002
08
6057cem
mktg3504
mthm036
mtrx1701
mth3241
eeee3086
cmp-7038b
cmp-7000a
ints4010
econ2151
infs5710
fins5516
fin3309
fins5510
gsoe9340
math2007
math2036
soee5010
mark3088
infs3605
elec9714
comp2271
ma214
comp2211
infs3604
600426
sit254
acct3091
bbt405
msin0116
com107/com113
mark5826
sit120
comp9021
eco2101
eeen40700
cs253
ece3114
ecmm447
chns3000
math377
itd102
comp9444
comp(2041|9044)
econ0060
econ7230
mgt001371
ecs-323
cs6250
mgdi60012
mdia2012
comm221001
comm5000
ma1008
engl642
econ241
com333
math367
mis201
nbs-7041x
meek16104
econ2003
comm1190
mbas902
comp-1027
dpst1091
comp7315
eppd1033
m06
ee3025
msci231
bb113/bbs1063
fc709
comp3425
comp9417
econ42915
cb9101
math1102e
chme0017
fc307
mkt60104
5522usst
litr1-uc6201.200
ee1102
cosc2803
math39512
omp9727
int2067/int5051
bsb151
mgt253
fc021
babs2202
mis2002s
phya21
18-213
cege0012
mdia1002
math38032
mech5125
07
cisc102
mgx3110
cs240
11175
fin3020s
eco3420
ictten622
comp9727
cpt111
de114102d
mgm320h5s
bafi1019
math21112
efim20036
mn-3503
fins5568
110.807
bcpm000028
info6030
bma0092
bcpm0054
math20212
ce335
cs365
cenv6141
ftec5580
math2010
ec3450
comm1170
ecmt1010
csci-ua.0480-003
econ12-200
ib3960
ectb60h3f
cs247—assignment
tk3163
ics3u
ib3j80
comp20008
comp9334
eppd1063
acct2343
cct109
isys1055/3412
math350-real
math2014
eec180
stat141b
econ2101
msinm014/msing014/msing014b
fit2004
comp643
bu1002
cm2030
联系我们
- QQ: 9951568
© 2021
www.rj363.com
软件定制开发网!