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Analyze the financial performance of your firm and, using historical financial statements for the last 5 years. Examine any relevant trends within your company over the past five years and compare your firm’s performance to the industry wherever possible. Focus on ratios that seem most relevant to the firm/industry, although you should look at ratios in each of the ratio groups. Since the definitions of some ratios vary by source and since sources such as finance.yahoo.com often combine numbers to simplify things, you need to calculate these ratios yourself. Morningstar provides this data in downloadable format for the past five years. Consequently, while the above analysis should be discussed in a text document (not more than two pages), you should also turn in ONE spreadsheet that includes:

1. A copy of the balance sheets and income statements from Morningstar for your company for the past 5 years. Ratios should be calculated directly within this spreadsheet, using cell formulas linked to the financial statement data, so that we can see exactly how each ratio is being calculated.

1. Some data is occasionally missing from the Morningstar download, in which case you might have to verify data in the company’s annual reports.

1. Include DuPont analysis for your firm

1. The definitions of the ratios that you used.

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# Essay help-ECON2233 Individual Homework 1

ECON2233 Individual Homework 1
(Due on Mar 17 Friday, by 12 noon)
10 points, equivalent to 5% of the unit’s assessments
1. Julio receives utility from consuming pizza (P) and movie (M) as given by the utility
function (,) = √, where P and M denote the amount of pizza and movie
Julio consumed. The marginal utility Julio receives from pizza and movie are given
as:      =

,
=

. The price of pizza and movie are given as      = 16
and
= 8, Julio has an income of \$96.
Show the derivation process that leads to the final solution for all parts of question.
a) What is Julio’s optimal bundle of pizza and movies that maximizes his utility?
And draw Julio’s indifference curve and budget constraint in a diagram and
identify the optimal bundle. Please show quantity of movies on x-axis and
quantity of pizzas on y-axis. (2 marks)
b) Holding the price of pizza and Julio’s income unchanged, what’s his new optimal
bundle when price of movie rises to \$12? What’s his new optimal bundle if price
of movie falls to \$6? Draw his new budget constraints in the previous diagram for
both scenarios and identify the optimal bundles. (2 marks) Derive the demand
curve for movies in a new diagram accordingly. (1 marks)
2. Jim spends most of his time in Coffee Club in Perth. Jim has \$24 per week to spend
on coffee and muffins. Coffee Club sells muffins for \$4 each and coffee for \$2.40 per
cup. He consumes cups of coffee and muffins per week.
a) Draw Jim’s budget constraint and label the axis properly. (1 marks)
b) Now Coffee Club introduces a frequent-buyer card: for every five cups coffee
purchased at the regular price of \$2.40 per cup, Jim receives a free sixth cup.
Draw Jim’s new budget constraint. (2 marks)
c) Does the introduction of the frequent-buyer card necessarily encourage Jim to
consume more coffee? Show how your answer depends on Jim’s preference map.
(2 marks)
word processing software. Label your graphs. If you absolutely cannot draw graphs in
software you can draw them by hand, ensure they are very clear, take a photo/scan and insert
them in your MSWord file. Writing all of the assignment by hand and scanning it in is not
appreciated – you should at least type in your non-graph parts of the answers.
Save a copy of your assignment as a backup.
Convert your assignment into a pdf file and upload them in the Assessments > Assessment 2
(home work 1) > Online Short Answer Homework link on LMS. You can submit only once,
so go over your work thoroughly before you pdf it and upload it.

# Buy Research Paper OnIine _PL4001 SOCIAL RESEARCH METHODS (USING SPSS)

Buy Research Paper OnIine _PL4001 SOCIAL RESEARCH METHODS (USING SPSS)

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IPL4001 SOCIAL RESEARCH METHODS

INSTRUCTIONS FOR QUANTITATIVE ASSIGNMENT

(Updated December/January 2017)

Quantitative research exercise 1,500 words (30%)

(LO 4, 5, 9, 10)

• Understand the processes involved in quantitative data collection and analysis
• Critically evaluate the significance of research findings in substantive area(s)
• Demonstrate research skills appropriate for quantitative research methods
• Demonstrate critical evaluation skills relevant to substantive research area(s)

Students will be expected to write up a short research report (1,500) on data collected as part of

a class exercise exploring Students’ Attitudes to Research.

The exercise will include the two main components

1. Setting up an SPSS database (this will be undertaken as part of a specific SPSS skills workshop). Please note that attendance at this workshop is strongly recommended regardless of the student’s level of skill in developing SPSS databases, as specific instructions on how to conduct descriptive statistics and ‘t-tests’ required for the report will be addressed in this workshop.

1. Producing a research report (1,500 words).

Students will be provided with completed MA/MSc students’ attitudes to research database.

This will be on myUniHub under the MA Social Work folder and the MSC Mental health Studies/Dual Diagnosis/MSc Complementary Health folders.

You will find the data under the module IPL4001 and SPSS Workshop Materials. The name of the file is ‘January SPSS Database 2017’.

The data will have been collected from students taking IPL4001 (Social Work and Health Students), who have been asked to complete an ‘attitudes to research’ questionnaire. Students will be expected to:

OUTLINE OF BRIEF RESEARCH REPORT ; please use the following format (Headings 1 to 5 below)

Heading 1       –           Introduction/statement of the problem

Should include a short statement regarding the challenges of teaching research in undergraduate/post graduate courses and how in particular social work/nursing students are somewhat anxious about undertaking ‘quantitative research’.

Should include a short/brief review on current knowledge regarding post graduate student’s attitudes to research in general and specifically attitudes to the use of quantitative methods.  The expectation is that students include 3-4 references on current literature addressing this issue.

Sub heading 1             Sample – describe what type of sampling was undertaken e.g. purposeful,

convenience etc, size of study population

Sub heading 2             Setting – describe where the research took place e.g. University setting, Department of Mental Health and Social Work, etc

Sub heading 3             Instruments – describe the instrument used, including its reliability and validity. A copy of the scale ‘The Attitudes Towards Research Scale (ATR)’  can be located at http://www.stat.auckland.ac.nz/~iase/serj/SERJ4(1)_Papanastasiou.pdf

Or a copy of the pdf paper has been uploaded into the folder SPSS Workshop Materials

Sub heading 4             Data collection/procedure– describe how the data was collected e.g. questionnaires were distributed within the class room and students were given 10-15 minutes to complete etc…

Sub heading 5             Data analysis – provide an overview of what analysis was employed and rationale for the use of descriptive statistics and t-tests.  Students should not just describe the analysis e.g. the mean was calculate for age, but should offer information on why the mean is calculated.

Heading 4                   Findings or Results (Student can choose which term to use)

Should include all the study findings, including where relevant the use of histograms or tables.  Please note tables and graphs are not part of the word allowance and should not be in the appendix.  Please do not ‘discuss’ your results in this section, this should be only be in the discussion.  When reporting the results please ensure that you do not present the same results in different formats e.g. in the text, then in a table, and again in graph form.  The aim is to ‘pull out the relevant data’ (usually the most important finding), report this in the text and then refer the reader to the remaining findings in the table/graph/figure.

Results should be reported as follows

Sub heading 1             % Response rate (note: the total number of students who could have taken part over the number who actually took part e.g.

This year (2016 – 17) there are 70 students registered for the module; please check how many actually took part in the study on the database file

Sub heading 2             Sample profile (including gender, age, highest education qualification attained, previous research experience, course status)

Sub heading 3             Attitude profile (include the mean scores for total research attitude and five sub scales (Life, Career, Positive, Difficulty and Anxiety for study participants)(see notes on analyses on how you might tackle the analysis and presentation of findings

Sub heading 4             Results for Hypotheses 1 and 2

You should include a discussion and interpretation of key study findings and refer back to relevant material you cited in the Literature Review (Heading 2).

Students will be expected to produce descriptive statistics from the data provided.

How to analyse and profile sample

Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data.

Students should report on the following descriptive statistics (Heading 4 Sub heading 2)

• Overall response rate – please note that 70 students were registered on the module and thus potentially available to participate
• Gender – frequency/percent
• Mean age (including Standard Deviation, min and max)
• Highest education qualification attained – frequency/percent
• Previous research experience – frequency/percent
• Course status – frequency/percent

How to interpret and report the findings for Attitude towards Research (Heading 4, Sub heading 3)

• Mean score of total research attitude (including Standard Deviation, min and max)
• Mean score of each of the five sub-scales (including Standard Deviation, min and max)

Total Research Attitude (new variable created) is determined by adding up the scores of each of the 32 items on the questionnaire.  Given that the scale responses are between 1 (negative attitude) and 7 (positive attitude), the minimum score a respondent could achieve on this scale is 32 (i.e. 1×32) and maximum score will be 224 (i.e. 7 x 32) (neutral point = 96).  Hence to determine the meaning of the score a respondent gets using this scale i.e. total research attitude, the higher the score the more positive the attitude.

The ‘concept’ of attitude to research is multidimensional (i.e. 5 areas that make up total attitude) and the scale measures each dimension (e.g. Life, Anxiety, Difficulty, Career, and Positive) – please refer to the full paper by ELENA C. PAPANASTASIOU the researcher who developed the instrument for a more in depth explanation of development of each dimension/factor.   A copy of this paper has been uploaded as a pdf on myUniHub or you can download it at:  http://www.stat.auckland.ac.nz/~iase/serj/SERJ4(1)_Papanastasiou.pdf

It therefore is important to appreciate how the ‘total research attitude’ is reflected and to draw further meaning/understanding by exploring each dimension in its own right.  Hence each domain minimum and maximum scores need to be known so that the respondents score can be interpreted as positive or negative.  The following table below shows the range of possible minimum score (negative attitude) and maximum score (positive attitude) for each domain. (In practice, remember that this cohort’s actual results may not go as low as the minimum or as high as the maximum score for each item).

Life (4 items) (min score 4 max score 28) (neutral point 12)

Anxiety (8 items) (min score 8 max score 56) (neutral point 24)

Difficulty (3 items) (min score 3 max score 21) (neutral point 9)

Career (9 items) (min score 9 max score 63) (neutral point 27)

Positive (8 items) (min score 8 max score 56) (neutral point 24)

Reporting the findings in your research report

For the purposes of the research report, you are expected to report and interpret the mean score for overall research attitude for the entire group, and the mean score for each domain.

You have two options of determining how best to interpret the means of the overall attitude score and each of the subscales (domains).  You can work out the mean of the means by dividing the mean for each total subscale score by the number of items in each sub scales, this will give you a ‘mean of the means’ which will be somewhere between 1 and 7 ( the original range of scores that participants could give on the Likert scale).  If we accept that 4 is neutral i.e. neither positive or negative then you can interpret the scores against this.

The second way would be to subtract the mean score for each subscale from the median score for each subscale and determine whether the study participants scores are plus/minus – if plus i.e. higher than the median then you can interpret that this subscale is going in the direction of being positive and vice versa, you can also interpret which subscale appears to score the highest positive score.

How to analyse and interpret the Hypotheses (Heading 4, Sub heading 4)

In addition to undertaking the above, students will expected to address the following two hypotheses

H1 Attitudes to research are different between male and female students

H2 Students, with previous research experience (e.g. undergraduate, field experience) will have a more positive attitude towards research, than students who have no previous research experience.

This will be achieved by running an independent ’t-test’. This is the most commonly used method to evaluate the differences in means between two independent groups.

The test variable for each t-test will be ‘total research attitudes’ and the grouping variable for hypothesis 1 will be ‘gender’ (Group 1 – 1(i.e. male; Group 2 = 2 (i.e. female). The grouping variable for hypothesis 2 will be ‘researchexperience’ (Group 1 – 0 (i.e. no; Group 2 = 1 (i.e. yes).

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