# Need help-STAT2112.13

Need help-STAT2112.13
Quiz #
8
(last)
NAME:____________________GWID:G_________________
Fall 201
6
sba
(Take Home)
Due
on Tuesday office Hour (5pm)
Rome
Hall
Questions 1
3
are based on the following
quarterly
data collected on
the
average nights
foreign
tourists
spent in
Washington DC
area
from 2011
2016 (
quarterly
data)
.
Time
Average Stay (
nights
)
Mar
11
1
41.7
Jun
11
2
24
Sep
11
3
32.3
Dec
11
4
37.3
Mar
12
5
46.2
Jun
12
6
29.3
Sep
12
7
36.5
Dec
12
8
43
Mar
13
9
48.9
Jun
13
10
31.2
Sep
13
11
37.7
Dec
13
12
40.4
Mar
14
13
51.2
Jun
14
14
31.9
Sep
14
15
41
Dec
14
16
43.8
Mar
15
17
55.6
Jun
15
18
33.9
Sep
15
19
42.1
Dec
15
20
45.6
Mar
1
6
21
59.8
Jun
1
6
22
35.2
Sep
1
6
23
44.3
Dec
1
6
24
47.9
1.
Use
Exponential
Smoothing
with w=0.6
to
predict average
stay (
nights
)
by
foreign
tourists
during
four (4) quarters of
201
7
.
2.
Assuming there is a trend in the da
ta, use
appropriate
s
moothing
technique
with
coefficients
w=0.6 and ν=0.2
,
to
predict the
average
stay (
nights
)
by
foreign
tourists
during
four (4) quarters
of
201
7
.
3.
Which of the above two models do you prefer?
W
hy
?
th
is question.
4
.
Which one the
assumption
(if any) is/
are required for using
Kruskal
Wallis
test?
I
. We assume that the samples drawn from the population are random.
II
. We also assume tha
t the cases of each group are independent.
III
. The measurement scale for should be at least ordinal.
A. I, II but not III
B. I, I
I
I but not II
C. I, II and III
D.
Kruskal
Wallis
is a distribution free statistics and
therefore
no assumption is requir
ed.
Questions
5
6
are based on the following data
.
S
uppose weights of
an
exotic
plant (lbs) a
re
different based on treatments (no
treatment, fertilizer, irrigation, or fertilizer and irrigation). Each
weight samples that determined by the treatments is independent and random
.
W
e
ight samples
are not normally distributed.
NO
Fert
Irrig
F
&I
0.15
1.34
0.23
2.03
0.02
0.14
0.04
0.27
0.16
0.02
0.34
0.92
0.37
0.08
0.16
1.07
0.22
0.08
0.05
2.38
0.
0
2
2.38
5
. T
est whether the
weights
of plants
are different under the
treatments.
6. What is your conclusion and why
.
7
8
. Six
restaurant
food
critics
were randomly assigned to
all
four
restaurant
s (A, B,
C, and D)
and
o
n the scale of 0
100 (100 being the best)
Rater A B C D
1
70
61
82
74
2
77
75
88
76
3
76
67
90
80
4
80
63
96
76
5
84
66
92
84
6
78
68
98
86
Are
there any differences
among
the
restaurant
conclusion
with
objective
facts
/statistics
.
9
. Which of the following nonparametric tests can be used for a paired difference experiment?
a. The Wilcoxon Signed Ranks test.
b. The Sign test.
c.
The
Kruskal
Wallis test
d
. Spearman’s Rank Correlation test
10. The following table provides
M
ath and
English
scores
on 10
stu
d
ents
.
The relationship may
not be linear. Use
appropriate
statistics
to investigate the possible
ass
ociation
between these
scores
Exam
Scores
English
56
75
45
71
61
64
58
80
76
61
Maths
66
70
40
60
65
56
59
77
67
63

# Need help-Statistics Assignment:Geochemistry 1

Need help-Statistics Assignment:Geochemistry 1

Field and Laboratory Techniques in Geochemistry 1

Statistics Assignment

Question 1)  10%

The data for a digestion of Bolivian tailings are provided. The elements are grouped as majors, traces and rare earth elements. Produce, using the descriptive statistics command in Excel (or any other suitable programme), summary data for each of these three groupings (Mean, Standard Error, Median, Mode, Standard Deviation, Sample Variance, Kurtosis, Skewness, Range, Minimum, Maximum, Sum and Count).

The data should be presented in tabulated form.

Question 2)  10%

Explain, using a maximum of three sentences for each, what you understand by the terms: Mean, Standard Error, Median, Mode, Standard Deviation, Sample Variance, Kurtosis, Skewness, Range, Minimum, Maximum, Sum and Count.

Question 3)  10%

Calculate the precision for each element analysed. (Hint the copy and paste tool is very useful for formulae).

Question 4)   10%

The data for a digestion of Bolivian uncontaminated soil are provided. The elements are grouped as majors, traces and rare earth elements. Calculate the mean, standard deviation, standard error and median of the samples for each of these three categories. Comment on any elements which show a large median/mean difference (hint Bi might be worth comparing in this context; for example against a major element). Your answer should incorporate the word ‘outlier’.

Question 5)   10%

BCR-1 and JB-3 are soil CRM materials. They were digested at the same time and using exactly the same methodology as the samples themselves. Calculate the accuracy of the digestion by comparing the results with the given elemental concentrations of the reference materials (BCR-1 rv and JB-3 rv). Comment on the accuracy of the analysis.

Question 6)  25%

The data for chloride concentrations of Regent’s canal and Pennine stream water, as determined by Ion Chromatography (IC), are presented. The data to be analysed are those collected from the Regent’s canal (RC in the spreadsheet itself). To the right of the spreadsheet these data has been extracted to help you answer the following questions.

Question 6a) the samples were analysed at two dilutions: a hundred fold (*100) and neat (*1). Why do you think that such a difference was reported in concentration? Which of these ‘dilutions’ do you trust?

Question 6b) construct a calibration curve (hint, scatter graph). The calibration standards employed were made up to 10, 20, 40 and 60 mg L-1. Plot a suitable regression line and display the R2 value on the graph, from this calculate the Pearson correlation coefficient (hint this is a one-step transformation)

Question 6c) do you think that drift correction might be necessary? Plot a suitable scatter graph to illustrate your answer. Note there is not a definitive yes or no answer to this question. You will be awarded marks on the strength of your reasoning.

Question 6d), using the blank data determine the LOD and LOQ for the complete analytical run. Describe, in a maximum of four sentences, what is meant by the terms LOD and LOQ.

Question 6e) Determine the precision* and accuracy (hint, consider the CRM dilution factor) of the Regent’s canal data. The concentration of chloride in the Battle reference standard is as follows:

*Note there are two duplicate pairs: 1 and 1a together with 2 and 2a. Calculate the individual precisions and the combined overall precision by any appropriate method.

Question 7)  25%

The data provided are from a column experiment which investigated the evolution of pore water concentrations over a modelled twenty year period. The column was packed with uncontaminated Bolivian soil together with sulphide mine tailings.

Question 7a) Produce a correlation matrix encompassing all of the elements (hint spreadsheet 30 gives a suitable method and also remember to remove all non-numerical data).

Question 7b) Produce three scatter graphs from the data. The first should show a strong positive correlation, the second a negative correlation and the third show minimal correlation. For each of these graphs plot a regression line, produce a linear equation and a R2 value. From the latter obtain the value of r (Pearson’s correlation).

7c) Calculate a Spearman correlation coefficient for the Zn and Cd concentrations (hint, follow the ranking formulae given in spreadsheet 11).

When comparing the Pearson and Spearman correlation coefficient, which of the two is more sensitive to outliers? Looking at the formulae can you suggest a reason for your conclusion?

Pearson

Spearman

7d) Give an example, not necessarily from the scientific literature, of correlation not implying causation (hint, Wikipedia has a good page addressing this specific question).

Need help-Statistics Assignment:Geochemistry 1

# Purchase Assignment-Quantitative Methods for Decision Making

Purchase Assignment-Quantitative Methods for Decision Making

Department of Management and Marketing

Quantitative Methods for Decision Making

Project 1

Word report (the hand writing reports will not be accepted) that includes the following three parts:

Question 1:

An investment company has classified its clients according to their gender and the composition of their investment portfolio (bonds, stocks, or a diversified mix of bonds and stocks). The proportions of clients falling into the various categories are shown in the following table:

 Gender Portfolio composition B (Bonds) S (Stocks) D (Diversified) M (Male) 0.18 0.20 0.25 F (Female) 0.12 0.10 0.15

1. What is the probability that a randomly selected client is male and has a diversified portfolio?
2. Find the probability that a randomly selected client is male, given that the client has a diversified portfolio?
3. Find the probability that a randomly selected client is Female, given that the client has a portfolio is composed of Bonds?
4. Let us define the following two events:

E1: the investor is a male

E2: the portfolio is composed of Stocks.

Can we conclude that the events E1 and E2 are independent?

Question 2:

In a hotel chain, the average number of rooms rented daily during each month is 50 rooms. The population of rooms rented daily is assumed to be normally distributed with a standard deviation of 4 rooms. For a specific month of the year, what is the probability that the number of rented rooms, in that month, is between 45 and 60 rooms?

Question 3:

The University registrar office has got some data regarding a sample of 200 students among those enrolled in the MBA Program. The registrar notes that 50 students of the sample are holders of a bachelor degree in business administration. What is the probability that among this sample 20 students hold a bachelor in business administration?

Purchase Assignment-Quantitative Methods for Decision Making

# RES5115: RESEARCH PREPARATION: PRINCIPLES AND APPROACHES QUANTITATIVE ASSIGNMENT(SPSS)

1
SCHOOL OF SCIENCE
_______________________________________________________________________________________________
RES5115: RESEARCH PREPARATION: PRINCIPLES AND APPROACHES
QUANTITATIVE ASSIGNMENT
DUE DATE: Friday 28th of October 2016 before midnight
For this assignment, you are expected to perform all analyses using either SPSS or Excel/Real Statistics. However prior to this, you will need to generate your own sub-sample (unique to your student ID) from a larger sample using the random number generator in Microsoft Excel. To do this, you must first activate the Analysis ToolPak in Excel by following steps below.
Step 1: Open a new Excel spreadsheet as shown below.
2
Step 2: Go to File → Options.
Step 3: Click on Add-ins and then click Go…
3
Step 4: Select Analysis ToolPak and click OK.
You can now use the Analysis ToolPak under the Data tab by clicking on Data Analysis.
Note that the above steps are for Microsoft Excel 2010 and may differ slightly if you are using the 2013 version.
4
QUESTION 1 [25 MARKS]
BACKGROUND
A study was conducted to investigate the effects of short-term treatments with growth hormone (GH) on biochemical markers of bone metabolism in men with idiopathic osteoporosis. Subjects ranged in age from 32 to 57 years. Among the data collected were serum concentrations of insulin-like growth factor binding protein-3 at 0 and 7 days after the first injection and 1, 4, 8 and 12 weeks after the last injection (i.e. post- treatment) with GH. The serum concentration data for 116 men are given in the Excel file “Serum.xlsx”.
TASK 1 – SELECTING A SUB-SAMPLE
Open the Serum.xlsx data file as shown.
Click on the “Data” tab and then run the “Data Analysis” tool pack.
5
Select Random Number Generation and click OK.
Select “Uniform” in the drop-down menu next to “Distribution”. Then fill out the other boxes as shown. In the box corresponding to “Random Seed”, make sure you type the last two digits of your student ID here. This will ensure the set of random numbers is unique to you (unless someone else shares the same two numbers).
You should now be able to see 116 random numbers in Column H. Take note that your numbers will be different to those shown here.
Last two digits only
6
Highlight all the data in from Columns A to H using the mouse/keyboard. Then click on   and select Custom Sort…
Now click on  next to ColumnSort by and select (Column H). Make sure that under Order, it is set to Smallest to Largest. Then click OK.
The data are now sorted according to Column H. Again, note that what is shown here is very likely to be different to what you will have. Now, select the first 60 observations (i.e. Rows 2 to 61) from Columns A to G and copy this sub-sample across to SPSS or another Excel spreasheet (e.g. Sheet 2). These observations form the dataset that you will be working with for this question.
7
TASK 2 – ANALYSING THE DATA
(i) Use SPSS or Excel/Real Statistics and generate the necessary summary statistics and figures to describe the serum concentrations 0 and 7 days after the first GH injection. Proper interpretation of these output in the context of the problem is expected. (ii) Use the appropriate test in SPSS or Excel/Real Statistics and determine whether the GH treatment had any significant impact on serum concentration 7 days after the 1st injection. You will need to comment on the nature and extent of these differences (if any). Hypothesis statements are not necessary.  (iii) Confidence intervals should be presented and interpreted whenever possible. (iv) All relevant assumptions associated with your chosen test must be verified. (v) Repeat steps (i) – (iv), but in this instance compare the serum concentrations 1, 4, 8 and 12 weeks after the last GH injection. If the initial analysis suggests a difference, you will then need to perform a post hoc test to determine where the difference(s) lie. Hypothesis statements are not necessary. (vi) Based on the outcomes of the two analyses, comment on the short-term and post-treatment effect of GH treatment on serum concentrations.

8
QUESTION 2 [25 MARKS]
BACKGROUND
Mental illness within the Australian population is becoming more apparent. A nationwide survey in 2007 on mental health and wellbeing conducted by the Australian Bureau of Statistics (ABS) found that an estimated 3.2 million Australian (20% of the population between the ages of 16 and 85) had a mental disorder in the twelve months prior to the survey, and the estimated economic impact of mental health problems is up to \$20 billion each year.
The mental health of fly-in/fly-out (FIFO) workers in resources sector became a subject of interest in recent years. Although the financial reward is great, reports of FIFO practices negatively impacting the workers and their Australian families are not uncommon.
To determine the extent of the mental health problem in the resources industry, a health and well-being survey was carried at a particular mining company. In the survey are questions relating to the worker’s demographics, behaviour in the past twelve months, work/lifestyle/family-related issues and others.
Also included in the survey are the Kessler’s mental health questions which will allow one to clinically determine the severity of mental health problems for an individual. The Kessler questions were developed by Professor Kessler and Mroczek (1992) to assess the severity (“1 = None of the time”, “2 = A little of the time”, “3 = Some of the time”, “4 = Most of the time” or “5 = All of the time”) of anxiety and depression related symptoms experienced in the past month. Collectively, they are the Kessler 10 or K10 questions. A K10 score is calculated by summing the scores of the 10 questions. The minimum possible score is 10 (low distress) and the maximum being 50 (very high distress).
Suppose that you are interested in examining whether there is an association between worker’s behaviours and their distress levels in the past 12 months.  The items of interest are presented in Table 1 and the relevant survey data are given in the Excel file “Mental Health.xlsx”. Note that a blank entry represents a missing response.
Table 1   Items of interest in the Health and Well-Being questionnaire Over the past 12 month (1 = Daily; 2 = Weekly; 3 = Monthly; 4 = Once or Twice; 5 = Almost never) (1) How often have you felt worn out? (2) How often have you been emotionally drained? (3) How often have you been irritable? (4) How often have you had aches and pains? (5) How often have you argued with a work colleague? (6) How often have you felt anxious? (7) How often have you had no energy or enthusiasm? (8) How often have you had 6 or more standard drink in one session? (9) How often have you used prescription or non-prescription drugs? (10) How often have you missed a meal? (11) How often have you argued with friends or family? (12) How often have you had trouble sleeping? (13) How often have you exercised?
9
TASK 1 – SELECTING A SUB-SAMPLE
Open the Mental Health.xlsx data file as shown.
Click on the “Data” tab and then run the Analysis ToolPak by clicking on Data Analysis.
Select Random Number Generation and click OK.
10
Select “Uniform” in the drop-down menu next to “Distribution”. Then fill out the other boxes as shown. In the box corresponding to “Random Seed”, make sure you type the last two digits of your student ID here. This will ensure the set of random numbers is unique to you (unless someone else shares the same two numbers).
You should now be able to see 1269 random numbers in Column O. Take note that your numbers will be different to those shown here.
Last two digits only
11
Highlight all the data in from Columns A to O using the mouse/keyboard. Then click on   and select Custom Sort…
Now click on  next to Column → Sort by and select (Column O). Then click OK.
The data are now sorted according to Column O. Again, note that what is shown here (next page) is very likely to be different to what you will have.
12
Now, select the first 150 observations (i.e. Rows 1 to 151) from Columns A to N. Copy this sub-sample across to another spreadsheet (e.g. Sheet 2) in Excel. In the example below, Sheet 2 was renamed to Sub- sample.

13
TASK 2 – SELECTING ITEMS FROM THE QUESTIONNAIRE TO ANALYSE
Now that you have your sub-sample, here you will determine which THREE (3) of the 13 items to analyse. Again, go to the “Data” tab and then run the “Data Analysis” tool pack. Select “Random Number Generation” and click “OK”.
Now generate 13 random uniform numbers and store them in Column P of the sub-sample spreadsheet. In the “Random Seed” box, type the last two digits of your student ID again.
You should now be able to see 13 random numbers in Column P. Take note that your numbers will again be different to those shown here. Now, type the numbers 1 – 13 (to represent the items) in Column Q and right next to the random numbers that you have just generated.
Last two digits only
14
Now, highlight all the numbers in Columns P and Q using the mouse/keyboard. Then sort the numbers by
clicking  and then   Sort Smallest to Largest.
The first three numbers in Column Q refer to the items in Table 1 that you will need to analyse. In this example, these are items (1), (3) and (13). Copy the relevant data for the 3 items and the corresponding K10 scores across to SPSS or another Excel spreadsheet (e.g. Sheet 3). These observations form the dataset that you will be working with for this question.
TASK 3 – ANALYSING THE DATA
(i) Use SPSS or Excel/Real Statistics and generate all necessary summary statistics and figures to describe the relationship between the workers’ mental health (according to the K10 scores) and each of your selected items (make sure you consider each item separately from the others). Proper interpretation of these output in the context of the problem is expected. (ii) Use the appropriate test in SPSS or Excel/Real Statistics and determine whether there is a difference in distress levels across the response categories for these each of these items. If so, perform a post-hoc test to determine where the difference(s) lie. You will need to comment on the nature and extent of these differences (if any). Hypothesis statements are not necessary.  (iii) Confidence intervals should be presented and interpreted whenever possible. (iv) All relevant assumptions associated with your chosen test must be verified.  (v) Briefly comment on the practical implications of your findings and how they may be useful.
15
SUBMISSION GUIDELINES:
This assignment must be completed using either SPSS or Excel/Real Statistics. It is expected that your assignment solutions are presented in the context of the problem. Simply stating the numbers from the output table will not suffice. Examples of this are given on Blackboard in the Quantitative weekly folders corresponding to the workshop weeks. The write-up of your analyses must be presented in Microsoft Word in Times New Roman format with 11-pt font with single spacing and in grammatically correct English. The page margins must be 2 cm for all sides. Failure to do so will result in deduction of marks. Furthermore, no handwritten assignments will be accepted. Copy only the relevant outputs, tables and/or figures from SPSS or Excel across to the Word document. All tables and figures must be labelled appropriately. The write-up for each question (not each part) must not exceed THREE (3) pages (including all tables and figures). Any lines exceeding the three-page limit will not be considered or read. Your assignment submission will also need to include the dataset that is unique to your student ID, along with a cover page (see page 16).
You are reminded of the declaration
“I certify that the attached assignment is my own work and that any material drawn from other sources has been acknowledged”.
that you sign when you complete the coversheet. The assignment solutions must be your own work.
You must submit your completed assignment via Turnitin by Friday 28th of October 2016 before midnight. In the interests of fairness, submission extensions will be given only in exceptional circumstances, and then only in accordance with University rules (see page 17).
Note: If your datasets do not match the ones generated with your student ID (last two digits only), you will be awarded a mark of zero regardless of whether the analysis is correct.
SUBMISSION CHECKLIST:
Your submission will need to be a single document containing the following:
o Cover sheet (1 page) o Your solutions to Questions 1 and 2 (maximum of 3 pages per question). o Your datasets (No restriction)
MARKING GUIDELINES:
(1) Adherence to submission guidelines above (10%) (2) Correct selection and implementation of tests and with correct findings (30%) (3) Proper presentation and interpretation of results in the context of the study and objective(s) (30%) (4) Use of statistics to support and re-inforce findings and arguments (15%) (5) Spelling, grammar and overall narrative (15%)
The above marking guidelines are estimates and variations may occur. If a test is incorrectly chosen, then only a maximum of 10 marks is attainable.
16
ASSIGNMENT COVER SHEET Electronic or manual submission
Form:  SSC-115-06-08
UNIT CODE:        TITLE:
NAME OF STUDENT (PRINT CLEARLY)                          FAMILY NAME                                  FIRST NAME
STUDENT ID. NO.
NAME OF LECTURER (PRINT CLEARLY)

DUE DATE
Topic of assignment

Group or tutorial (if applicable)

Course

Campus

I certify that the attached assignment is my own work and that any material drawn from other sources has been acknowledged.   Copyright in assignments remains my property.  I grant permission to the University to make copies of assignments for assessment, review and/or record keeping purposes.  I note that the University reserves the right to check my assignment for plagiarism.  Should the reproduction of all or part of an assignment be required by the University for any purpose other than those mentioned above, appropriate authorisation will be sought from me on the relevant form.
OFFICE USE ONLY
If handing in an assignment in a paper or other physical form, sign here to indicate that you have read this form, filled it in completely and that you certify as above.
Signature Date
OR, if submitting this paper electronically as per instructions for the unit, place an ‘X’ in the box below to indicate that you have read this form and filled it in completely and that you certify as above.  Please include this page in/with your submission.   Any electronic responses to this submission will be sent to your ECU email address. Agreement                    Date
PROCEDURES AND PENALTIES ON LATE ASSIGNMENTS (University Rule 39)  A student who wishes to defer the submission of an assignment must apply to the lecturer in charge of the relevant unit or course for an extension of the time within which to submit the assignment. (39.1)  Where an extension is sought for the submission of an assignment the application must:  be in writing  –  preferably before the due date; and   set out the grounds on which deferral is sought. ( see 39.2)  Assignments submitted after the normal or extended date without approval shall incur a penalty of loss of marks. (see 39.5) ACADEMIC MISCONDUCT (University Rule 40) All forms of cheating, plagiarism or collusion are regarded seriously and could result in penalties including loss of marks, exclusion from the unit or cancellation of enrolment. – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –
ASSIGNMENT RECEIPT       To be completed by the student if the receipt is required
UNIT

NAME OF STUDENT

STUDENT ID. NO.

NAME OF LECTURER

Topic of assignment

17
CONDITIONS FOR ASSIGNMENT EXTENSION
In accordance with ECU policy, extensions are given on the following grounds and must include all appropriate supporting documentation:
 Ill health or injury for an extended period of time – medical certificate is required;  Compassionate grounds – supporting documentation includes e.g. newspaper notice plus other evidence if not the same family name, e.g. marriage certificate;  Representation in sporting activities at a national or international level;  Representation in significant cultural activities;  Employment related intrastate, interstate and overseas travel – a letter from your employer, including your supervisors’ full contact details.
The following factors will NOT be considered as grounds for extension:
 Routine demands of employment;  Stress or anxiety normally associated with examinations, required assessments or any aspect of course work;  Routine financial support needs;  Lack of knowledge of the requirements of academic work;  Difficulties with English language;  Scheduled anticipated changes of address, moving home etc;  Demands of sport, clubs, social or extra-curricular activity other than those specified above;  Recreational travel (domestic or international);  Planned events such as weddings, birthday parties etc;  Misreading the deadline.
All extension requests will require students to complete the Assignment Extension Form (downloadable from the Quantitative Assignment folder on BB), along with appropriate documentation such as a medical certificate, letter from employer, etc. Original copies of these documents will then need to be provided. Scanned or photocopied documents are NOT acceptable. All documents must be provided no longer than ONE week after the assignment deadline.

# Assignment Help-Statistics

Assignment Help-Statistics

PART B: Correlation and Regression

These instructions apply to the following problems.

(a) Draw the scatter plot for the variables.

(b) Compute the correlation coefficient. Use three decimal places.

(c) Find the equation of the regression line.

(d) Find the predicted y-value for the specified x-value.

Use technology.

1. Consider the data.
 X 160 227 140 144 161 147 141 Y 189 157 140 127 123 106 101

Find y-predicted when x = 170.

Week 7 Homework Assignments

1.  This week we must read

Lane et al. Chapters 14 & 17
Illowsky et al. Chapters 11 & 12

1.  Do the four problems listed in the table below.
 eResources Chapter Problem Page* Lane et al. 17 5 613 Chi-square Goodness of Fit 14 616 Chi-square test of Independence Illowski et al. 11 102 623 Chi-square test of Homogeneity 12 82 687 Regression

Assignment Help-Statistics

# Need Help-Statistics Assignment

Need Help-Statistics Assignment
Statistical Inference I: J. Lee
Assignment 3
Problem 1.
Approximately 80,000 marriages took place in the state of Pennsylvania last year. Estimate
the probability that, for at least one of the couples married in PA last year,
(a) both partners were born on April 30;
(b) both partners celebrated their birthday on the same day of the year.
Make sure to state what assumptions you are making in your computation.
Problem 2.
A certain typing agency employs Al, Bob, and Cathy as typists. The average number of errors
per page is 3 when typed by Al, 4.2 when typed by Bob, and 2.1 when typed by Cathy. If your 7-page article
is equally likely to be typed by any of the three typists, estimate the probability that it will have no errors.
Also estimate the probability it will have at most 3 errors.
Problem 3.
Let
X
denote the lifetime (in hours) of a light bulb, and assume that the density function of
X
is given by
f
(
x
) =
8
<
:
2
x
if 0
x <
1
=
2
3
=
4
if 2
< x <
3
0
otherwise.
(a) On average, what fraction of light bulbs last more than 15 minutes?
(b) Compute
E
(
X
).
(c) Compute
P
(0
:
25
< X
2
:
2
j
X >
1)
:
(d) Compute
P
(
X
= 2)
; P
(
X
= 0)
; P
(
X
=
E
(
X
))
:
Problem 4.
The density function of
X
is given by
f
(
x
) =
a
+
bx
2
if 0
x
1
0
otherwise.
Suppose also that you are told that
E
(
X
) = 3
=
5
:
(a) Find
a
and
b
.
(b) Determine the cdf,
F
(
x
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Problem 5.
De ne the function
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by
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:
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if
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if 1
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if
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:
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make a modi cation to
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so that it is a cdf, and then compute the corresponding pdf.
(c) Compute the expectation of
X
, if
X
has density given by the pdf from part (b).
1
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# Statistice; Topic of the quantitative research exercise

Statistice; Topic of the quantitative research exercise

Topic of the quantitative research exercise

Imagine you are taking part in a project exploring Middlesex University’s undergraduate students’ use of social networking sites (SNS).

The overall objectives of the study are as follows:

• Explore how students use SNS
• Test whether or not there is any statistical association between student’s use of SNS and their personal characteristics (e.g. age, gender, year of study, etc.)
• Test whether or not there is a statistically significant relationship between student’s use of SNS and their academic learning

Within this broad objective, you may want to give your study a clearer focus – looking into a specific aspect or, for example, building on what you have learned with your earlier qualitative exercise.

As an experienced quantitative researcher you have been asked to conduct a survey, based on a structured questionnaire. A crucial  part of good research design concerns making sure that the questionnaire design addresses the needs and the objectives of the research. In other words, it is important to ensure that the questions asked are the right ones.

# 1. Design a questionnaire, which must include:

1. An introduction to the research, the researcher and explain any confidentiality issues;
2. 10 questions (=10 variables) which relate to the objectives of the research.

Different types of questions should be used, e.g. closed, single vs. multiple responses, ranking, and rating.  Due to the difficulty of analysing open responses, you should not include open-ended questions in your questionnaire. Moreover, when designing your questionnaire it is imperative that you take into consideration the types of statistical methods that you wish to use to analyse your data once it is collected.

Note: Before setting-up the questionnaire for data-collection with SurveyMonkey (next task), it is advisable that you pilot (or ‘pretest’) your questionnaire, using a paper version of it. Piloting is a crucial step to ensure any kind of error or problem associated with survey research are reduced before you start collecting the data. This will help you to improve the quality of data significantly.

Pilots are usually conducted on a small sample of respondents  from the target population. Here you can pretest your questionnaire on at least one (1) student. Based on how it goes you may decide to revise the questionnaire and then move to data collection.

# 2. Set-up and administer an online questionnaire with SurveyMonkey

• Register for a free SurveyMonkey account (all information about SurveyMonkey are available here: http://www.surveymonkey.com)
• Set-up your on-line questionnaire (based on what you designed in task 1)
• Send a link to your SurveyMonkey survey to fellow students in order to collect 20 completed questionnaires. (You should ensure you get a well- balanced sample – e.g. 10 males and 10 females – also depending on what your variables are).

For this part, please provide me with the table of all data. You may just make up the possible answers for all survey questions reasonably and I will then create a surveymonkey account to enter the data myself.

# 3. Enter and analyse your results into SPSS

• Enter the data from SurveyMonkey into and SPSS data file (ways to do this will be discussed during the seminars)
• Ensure the dataset is properly organised and that all variables are coded properly (e.g. for gender, you could use male=1 and female = 2). Always double check both the ‘Variable view’ and ‘Data view’ in SPSS.
• Analyse the data-set with SPSS, producing outputs tables (which you should include in your report, see next task)

# 4. Write a brief reflective report (1000-1500 words)

The report must include the following parts:

• Introduction to the study, including aim and objectives;
• Survey methodology including: how you have determined a certain set of questions and responses to those questions; sampling criteria; issues of confidentiality
• Presentation and discussion of results of the survey, with tables and comments (n.b. tables are not included in the word count)
• A description of your experience of conducting a survey, reflecting on the advantages and disadvantages of such an approach.
• References (Note: it is important that you draw on the relevant and appropriate literature in your reflective report. So please ensure that you add the appropriate references at the end of the report)
• Your questionnaire (at the end, as an appendix – not included in the word count).

# Assessment Criteria:

• Your work will be judged on the extent to which you have addressed all the requirements successfully. Your lecturer will specifically assess the following:
• You developed a structured questionnaire using SurveyMonkey, based on ten questions that meet the objectives of the study. [15 marks]
• You have surveyed 20 students successfully, using SurveyMonkey [10 marks]
• You have entered the data into SPSS and coded the variables properly [10 marks]
• You have appropriately conducted and presented  data-analysis (e.g. creating and commenting on frequency distribution tables for all variables). [10 marks]
• You have tested and discussed whether there is any statistically significant relationship between relevant variables (including Chi-squared test). [10 marks]
• Your report is properly structured and presented  (including tables as appropriate) [10 marks]
• Your report discusses aims, objectives and methodological issues [15 marks]
• Your report includes a description of your work and experience [10 marks]
• Your report includes appropriate referencing [10 marks]