The document provides guidance on analyzing survey results from a market research project. It discusses analyzing data at different levels of depth to uncover meaningful insights. Scenarios show how initial conclusions may change with deeper analysis considering additional variables like gender and age group. Students are instructed to analyze a sample survey data set to practice these concepts. They should look for trends, patterns, correlations and consider what other data could have been collected. The goal is for students to draw valid conclusions and propose improvements to their product based on the survey analysis.
A presentation outlining what primary research is and how to conduct and analyze it. The presentation compares primary and secondary research. It walks the audience through selecting research objectives and methods, how to draft a study, and how to recruit appropriate respondents. It discusses interview techniques and provides some basics on analyzing data and drawing conclusions. This presentation is aimed at start-ups and entrepreneurs looking to conduct their own research on modest budgets and timelines.
Survey Methodology and Questionnaire Design Theory Part IQualtrics
Do you know what's going on in your respondents' heads as they take your survey? How can you design your questionnaire to collect better data? Understanding the answers to these questions can help you design surveys that collect high quality insights you can depend on.
Dave Vannette, principal research scientist at Qualtrics, shares his best hacks for designing surveys that will help you get quality data. In this presentation, Dave also highlights what your respondents are thinking when they take your surveys, and how your survey design can affect the responses you collect.
A presentation outlining what primary research is and how to conduct and analyze it. The presentation compares primary and secondary research. It walks the audience through selecting research objectives and methods, how to draft a study, and how to recruit appropriate respondents. It discusses interview techniques and provides some basics on analyzing data and drawing conclusions. This presentation is aimed at start-ups and entrepreneurs looking to conduct their own research on modest budgets and timelines.
Survey Methodology and Questionnaire Design Theory Part IQualtrics
Do you know what's going on in your respondents' heads as they take your survey? How can you design your questionnaire to collect better data? Understanding the answers to these questions can help you design surveys that collect high quality insights you can depend on.
Dave Vannette, principal research scientist at Qualtrics, shares his best hacks for designing surveys that will help you get quality data. In this presentation, Dave also highlights what your respondents are thinking when they take your surveys, and how your survey design can affect the responses you collect.
Survey Methodology and Questionnaire Design Theory Part IIQualtrics
This is part two to Dave Vannette's presentation on survey methodology and questionnaire design theory. In this presentation dave goes into more detail on response options and question wording.
Best Practices for the Academic User: Maximizing the Impact of Your Instituti...Qualtrics
To view the on-demand webinar for this presentation see the following link: https://success.qualtrics.com/academic-best-practices-watch.html
Qualtrics has changed the landscape for colleges and universities, introducing many features to help academic decision makers run more successful surveys.
Join Qualtrics and Jag Patel, Associate Director of Institutional Research at MIT, as we share best practices and tips for academic users.
For more classes visit
www.snaptutorial.com
PSYCH 625 Assignment Week 1 Descriptive and Inferential Statistics Worksheet (New Syllabus)
PSYCH 625 Assignment Week 2 Probability and Statistical Analysis Worksheet (New Syllabus)
PSYCH 625 Assignment Week 3 Identifying Statistical Tests in the Literature Worksheet (New Syllabus)
PSYCH 625 Assignment Week 4 Comparing Means Worksheet (New Syllabus)
Representing and generating uncertainty effectively presentatıonAzdeen Najah
Prof. Frank H Knight (1921) proposed that "risk" is randomness with knowable probabilities, and "uncertainty" is randomness with unknowable probabilities. However, risk and uncertainty both share features with randomness. The illustration here explains the relationship of the concepts better than words...
Startup Class - Identifying Your Market Needsstartupclass
Triin Mahlakõiv talks us through the customer development framework and how to use the business canvas model correctly. Triin is the Startup Community Lead at the Tallinn Science Park Tehnopol.
Survey Methodology and Questionnaire Design Theory Part IIQualtrics
This is part two to Dave Vannette's presentation on survey methodology and questionnaire design theory. In this presentation dave goes into more detail on response options and question wording.
Best Practices for the Academic User: Maximizing the Impact of Your Instituti...Qualtrics
To view the on-demand webinar for this presentation see the following link: https://success.qualtrics.com/academic-best-practices-watch.html
Qualtrics has changed the landscape for colleges and universities, introducing many features to help academic decision makers run more successful surveys.
Join Qualtrics and Jag Patel, Associate Director of Institutional Research at MIT, as we share best practices and tips for academic users.
For more classes visit
www.snaptutorial.com
PSYCH 625 Assignment Week 1 Descriptive and Inferential Statistics Worksheet (New Syllabus)
PSYCH 625 Assignment Week 2 Probability and Statistical Analysis Worksheet (New Syllabus)
PSYCH 625 Assignment Week 3 Identifying Statistical Tests in the Literature Worksheet (New Syllabus)
PSYCH 625 Assignment Week 4 Comparing Means Worksheet (New Syllabus)
Representing and generating uncertainty effectively presentatıonAzdeen Najah
Prof. Frank H Knight (1921) proposed that "risk" is randomness with knowable probabilities, and "uncertainty" is randomness with unknowable probabilities. However, risk and uncertainty both share features with randomness. The illustration here explains the relationship of the concepts better than words...
Startup Class - Identifying Your Market Needsstartupclass
Triin Mahlakõiv talks us through the customer development framework and how to use the business canvas model correctly. Triin is the Startup Community Lead at the Tallinn Science Park Tehnopol.
This is a modified version of Master Class that Dr Siobhan O'Dwyer delivered at the Griffith University School of Nursing's Annual Research School for postgraduate students.
Remarks from the professor on milestone 1 and for milestone 2A.docxsodhi3
Remarks from the professor on milestone 1 and for milestone 2
A good start on the paper. Please look at the introduction again. It does not match the case problem or what the issues of the company are. If you look at the first paragraph it does not lead into the next paragraph and the facts and flow are disjointed.
I read through the paper and it is a series of unjoined statements that don't really flow into a research work. You do have the correct issue that monthly variance in demand is the key to solving the problem but the supporting work for this statement is not there.
The next step for milestone 2 is to analyze the descriptive statistics, ANOVA and correlation/regression asked for in the case. From that you should see how to develop a model to correct the forecasting problem. Make sure your Milestone 2, gives a model that solves the problem.
QSO 510 Milestone Two Guidelines and Rubric
The final project for this course is the creation of a statistical analysis report. Operations management professionals are often relied upon to make decisions
regarding operational processes. Those who utilize a data-driven, structured approach have a clear advantage over those offering decisions based solely on
intuition. You will be provided with a scenario often encountered by an operations manager. Your task is to review the “A-Cat Corp.: Forecasting” scenario, the
addendum, and the accompanying data in the case scenario and addendum.
In Module Seven, you will submit your selection of statistical tools and data analysis, which are critical elements III and IV. You will submit a 3- to 4-page paper
and a spreadsheet that provides justification for the appropriate statistical tools needed to analyze the company’s data, a hypothesis, the results of your analysis,
any inferences from your hypothesis test, and a forecasting model that addresses the company’s problem.
Specifically, the following critical elements must be addressed:
III. Identify statistical tools and methods to collect data:
A. Identify the appropriate family of statistical tools that you will use to perform your analysis. What are your statistical assumptions concerning
the data that led you to selecting this family of tools? In other words, why did you select this family of tools for statistical analysis?
B. Determine the category of the provided data in the given case study. Be sure to justify why the data fits into this category type. What is the
relationship between the type of data and the tools?
C. From the identified family of statistical tools, select the most appropriate tool(s) for analyzing the data provided in the given case study.
D. Justify why you chose this tool to analyze the data. Be sure to include how this tool will help predict the use of the data in driving decisions.
E. Describe the quantitative method that will best inform data-driven decisions. Be sure to include how this method will point out the relationships
between ...
BUSI 230Discussion Board Forum 1Project 2 InstructionsSta.docxRAHUL126667
BUSI 230
Discussion Board Forum 1/Project 2 Instructions
Standard Deviation and Outliers
Thread:
For this assignment, you will use the Project 2 Excel Spreadsheet to answer the questions below. In each question, use the spreadsheet to create the graphs as described and then answer the question.
Put all of your answers into a thread posted in Discussion Board Forum 1/Project 2.
This course utilizes the Post-First feature in all Discussion Board Forums. This means you will only be able to read and interact with your classmates’ threads after you have submitted your thread in response to the provided prompt. For additional information on Post-First, click here for a tutorial. This is intentional. You must use your own work for answers to Questions 1–5. If something happens that leads you to want to make a second post for any of your answers to Questions 1–5, you must get permission from your instructor.
1. A. Create a set of 5 points that are very close together and record the standard deviation. Next, add a sixth point that is far away from the original 5 and record the new standard deviation.
What is the impact of the new point on the standard deviation? Do not just give a numerical value for the change. Explain in sentence form what happened to the standard deviation. (4 points)
B. Create a data set with 8 points in it that has a mean of approximately 10 and a standard deviation of approximately 1. Use the second chart to create a second data set with 8 points that has a mean of approximately 10 and a standard deviation of approximately 4. What did you do differently to create the data set with the larger standard deviation? (4 points)
2. Go back to the spreadsheet and clear the data values from Question 1 from the data column and then put values matching the following data set into the data column for the first graph. (8 points)
50, 50, 50, 50, 50.
Notice that the standard deviation is 0. Explain why the standard deviation for this one is zero. Do not show the calculation. Explain in words why the standard deviation is zero when all of the points are the same. If you don’t know why, try doing the calculation by hand to see what is happening. If that does not make it clear, try doing a little research on standard deviation and see what it is measuring and then look again at the data set for this question.
3. Go back to the spreadsheet one last time and put each of the following three data sets into one of the graphs. Record what the standard deviation is for each data set and answer the questions below.
Data set 1:
0, 0, 0, 100, 100, 100
Data set 2:
0, 20, 40, 60, 80, 100
Data set 3:
0, 40, 45, 55, 60, 100
Note that all three data sets have a median of 50. Notice how spread out the points are in each data set and compare this to the standard deviations for the data sets. Describe the relationship you see between the amount of spread and the size of the standard deviation and explain why this connection exists. Do not give your calcu ...
ANOVA is a hypothesis testing technique used to compare the equali.docxjustine1simpson78276
ANOVA is a hypothesis testing technique used to compare the equality of means for two or more groups; for example, it can be used to test that the mean number of computer chips produced by a company on each of the day, evening, and night shifts is the same. Give an example of an application of ANOVA in an industrial, operations, or manufacturing setting that is different from the examples provided in the overview. Discuss and share this information with your classmates.
In responding to your peers, select responses that use an ANOVA application that is different from your own. Are the results of the ANOVA application statistically significant? Why are the results significant or not significant? Explain your reasoning. Consider how ANOVA could be applied to the final project case study.
Support your initial posts and response posts with scholarly sources cited in APA style.
https://statistics4beginners.wordpress.com/2015/02/18/how-to-calculate-anova-in-excel-2013/
PLEASE GIVE A 1-2 PARAGRAPH RESPONSE TO THE FOLLOWING:
1.
In this module, our goal is to learn the statistical process of comparing several population means through a procedure called "analysis of variance", or ANOVA. ANOVA uses the variance from the mean of 2 or more sample populations to see if there is a statistically significant difference between them (Sharpe, DeVeaux, Velleman, 2016). We've learned that this is a valuable tool in all sorts of areas of study, including automotive, chemical, and medical industries.
There are many practical examples of ANOVA throughout business. As previously mentioned, the medical field can benefit from the use of this statistics tool. For example, a drug company may be interested in the results of clinical trials for a few new drugs they plan to release. Medicine A, B, and C are all now in the clinical testing phase, so the instances in which each cures a specific ailment can be summed up using ANOVA. Each of the individual drugs, through the course of multiple trials, will have a number of "cured" patients. The following is an example of what the results may be, in table format:
A B C
Trial 1 4 9 2
2 5 8 7
3 7 1 6
4 6 1 5
5 6 4 9
Using ANOVA to evaluate the variance from the mean for each trial, the ultimate goal would be to compare each trial to one another. By comparing the variance, we can say, with statistical confidence, that one medicine may be more effect.
PSYCH 625 MENTOR Education Your Life / psych625mentor.comkopiko27
FOR MORE CLASSES VISIT
www.psych625mentor.com
PSYCH 625 Week 1 Individual Assignment Basic Concepts in Statistics Worksheet
PSYCH 625 Week 1 Individual Assignment Reliability and Validity Matrix
PSYCH 625 Week 1 Individual Assignment Time to Practice – Week One
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tutor2u Strong Foundations A Level Psychologytutor2u
Browse the student workshop booklet for our A Level Psychology Strong Foundations exam-skills and revision workshop. For more information on how to attend the A Level Psychology Strong Foundations workshops, please visit http://www.tutor2u.net/events/a-level-psychology-strong-foundations-workshops
Assessment Information Subject Code BUS605 Subject.docxjesuslightbody
Assessment Information
Subject Code: BUS605
Subject Name: Business Research Methodology and Data Collection
Assessment Title: Assessment 3 – Hypotheses testing (Individual Written Report)
Weighting: 35 %
Total Marks:
Length:
35
2500 (+- 10%)
Due Date: Submission due Week 12 – Sunday at 11.59 pm
COURSE: Master of Business (Research)
Unit: Business Research Methodology and Data Collection
Unit Code: BUS605
Type of Assessment: Assessment 3 – Individual Written Report
Unit Learning
Outcomes
addressed:
(a) Demonstrate an advanced ability to identify, assimilate, and
review applications of, particular research techniques.
(b) Identify various means of data collection that are feasible and
can be ethically enacted.
(c) Articulate and critically evaluate differences between alternative
research methodologies.
(d) Explain how research outcomes may be affected by the nature
and application of particular research techniques.
(e) Demonstrate an advanced ability to construct a robust
methodology for addressing a research question.
(f) Explain how the use of selected methodologies is relevant to a
specific research proposal.
Criteria for
Assessment:
Preliminary analysis
Hypothesis testing and data analysis
Interpretation of findings
Academic writing
Submission Date: Week 12 Sunday at 11.59 pm
Total Mark &
Weighting:
35 marks | 35%
Students are advised that any submissions past the due date without an approved extension
or approved extenuating circumstances incur a 5% penalty per calendar day,
calculated from the total mark e.g. a task marked out of 15 will incur a 1.75-mark penalty per
calendar day.
Task description
Scenario
Uber, a ridesharing service company has recently entered the Nepalese market, and its service has
been received by some people. Like any product or service, customers’ adoption and usage are
essential for the survival of the firm. Thus, like any other services, there might many factors that have
influenced riders to adopt and use Uber services. However, from the existing literature, empirical studies
on factors determining ridesharing service adoption is scarce, especially in emerging economies. Thus,
a study is being conducted to address this gap in the literature. The social exchange theory forms the
basis of the study. The researcher designed the research model shown in figure 1 and developed
hypotheses H1-H5(see below the research model). Based on the research model shown in figure 1,
data was collected from some Uber riders in Nepal. The data is available in Exo (see Week 12 folder).
Figure1: Research Model
Hypotheses(H)
H1: Consumer need for prestige has a positive effect on riders’ continuous usage intentions
H2: Trust has a positive effect on riders’ continuous usage intentions
H3: Customer return investment has a positive effect on riders’ continuous usage intentions
H4: Convenience has a p.
5/25/2020 Rubric Detail – 31228.202030
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Rubric Detail
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and made it available to you. Select Grid View or List View to change the rubric's layout.
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Name: ITS836 (8 Week) Research Paper Rubric
Description: Please use this rubric for grading research papers
Exit
Grid View List View
No requirements are met
Includes a few of the required components as speci�ed in the assignment.
Includes some of the required components as speci�ed in the assignment.
Includes most of the required components as speci�ed in the assignment.
Includes all of the required components as speci�ed in the assignment.
Requirements
--
No Evidence 0 (0.00%) points
Limited Evidence 3 (3.00%) points
Below Expectations 7 (7.00%) points
Approaches Expectations 11 (11.00%) points
Meets Expectations 15 (15.00%) points
Fails to provide enough content to show a demonstration of knowledge
Major errors or omissions in demonstration of knowledge.
Some signi�cant but not major errors or omissions in demonstration of knowledge.
A few errors or omissions in demonstration of knowledge.
Demonstrates strong or adequate knowledge of the materials; correctly represents knowledge
from the readings and sources.
Content
--
No Evidence 0 (0.00%) points
Limited Evidence 3 (3.00%) points
Below Expectations 7 (7.00%) points
Approaches Expectations 11 (11.00%) points
Meets Expectations 15 (15.00%) points
5/25/2020 Rubric Detail – 31228.202030
https://ucumberlands.blackboard.com/webapps/rubric/do/course/gradeRubric?mode=grid&isPopup=true&rubricCount=1&prefix=_843783_1&course_i… 2/4
g
Fails to provide a critical thinking analysis and interpretation
Major errors or omissions in analysis and interpretation.
Some signi�cant but not major errors or omissions in analysis and interpretation.
A few errors or omissions in analysis and interpretation.
Provides a strong critical analysis and interpretation of the information given.
Critical Analysis
--
No Evidence 0 (0.00%) points
Limited Evidence 5 (5.00%) points
Below Expectations 10 (10.00%) points
Approaches Expectations 15 (15.00%) points
Meets Expectations 20 (20.00%) points
Fails to demonstrate problem solving.
Major errors or omissions in problem solving.
Some signi�cant but not major errors or omissions in problem solving.
A few errors or omissions in problem solving.
Demonstrates strong or adequate thought and insight in problem solving.
Problem Solving
--
No Evidence 0 (0.00%) points
Limited Evidence 5 (5.00%) points
Below Expectations 10 (10.00%) points
Approaches Expectations 15 (15.00%) points
Meets Expectations 20 (20.00%) points
Source or example selection and integration of knowledge.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
2. Re-capping Last Lesson
O Understand the need for market research
O Design a survey with 10 questions to
evaluate the acceptance/ demand for your
product by potential customers
O Find out your respondents’ thoughts/
comments in relation to your product’s
features (unique selling points), pricing,
how helpful it is, how helpful it can be, etc
O Collected at least 30 survey responses
3. Today
O Analyze the results of the market survey
done in Lesson 4
O Draw valid conclusions and insights based
on the analysis, and propose
improvement to the product accordingly
4. By the end of the next lesson,
you will need to submit…
O Survey objectives (Introduction of your survey)
O Survey questions
O Raw data in MS Excel (generated from Google docs)
O Pie Charts/ Graphs (generated from Google docs or
excel)
O Survey analysis
O A short write-up on improvements made to the
original idea after doing the survey analysis
O A sketch of the improved idea
5. Last lesson ASST 2 – 15%
Survey
Grading
Far Exceeds
Expectations
Exceeds
Expectations
Meets
Expectations
Below
Expectations
Far Below
Expectations
Design,
Structure &
Objectives
of
Questions
All or most (>=90%)
questions logically
sequenced and well
designed, with
appropriate choice of
formatting and
grammatically correct.
All or most questions
designed to meet
research objectives.
At least 70% of
questions
logically
sequenced and
well designed,
with appropriate
choice of
formatting and
grammatically
correct. 7-8
questions
purposely
designed.
At least 50% of
the questions
are logically
sequenced and
well designed,
with appropriate
choice of
formatting and
grammatically
correct. 5-6
questions
purposely
designed.
Few questions
(30-40%) are
logically
sequenced and
well designed,
with appropriate
choice of
formatting and
grammatically
correct. Few
questions
purposely
designed.
> 70% illogically
sequenced,
ambiguous, with
frequent
mistakes made
in choice of
formatting and
grammar. Most
questions are off
tangent or not
known.
5 4 3 2
1-2 logically
sequenced,
correctly
formatted and
grammatically
sound questions
= 1 mark; zero
questions = 0
mark
6. This lesson – ASST 2 cont.
Analysis
Grading
Far Exceeds
Expectations
Exceeds
Expectations
Meets
Expectations
Below
Expectations
Far Below
Expectations
Sense-making
(*open-ended Qns,
only if applicable)
Close-ended Qns:
Strong meaningful
information based on
logical inferences
from data collected.
*Open-ended Qns:
Data is grouped in
meaningful
categories and is
accurate. Very deep
insights into
consumers' wants
and needs analysed
Close-ended Qns:
Good meaningful
information inferred
from data. Can be
more logical/ clearer in
the information
derived. *Open-ended
Qns: Data is grouped
in meaningful
categories and mostly
accurate. Good depth
in understanding
insight into consumers'
needs and wants.
Close-ended
Qns: Sufficiently
described data,
without further
attempt to infer
deeper. *Open-ended
Qns:
Sufficient attempt
to group data in
categories
accurately. No
further inference
done.
Surface data
reported as it is
without further
attempt to
categorise
*open-ended
qns, or infer
deeper for the
close-ended qns.
Noticeable
omissions and/or
inaccuracies in
data (< 50%).
Data described
without further
attempt to
categorise *open-ended
Qns, or infer
deeper from the
close-ended Qns.
Huge omissions
and/ or inaccuracies
in data (> 50%) = 1
mark; No attempt to
analyse or report
results = 0 mark
5 4 3 2 0 - 1
Recommendations
of feedback (for or
against customer
feedback analysis)
All changes
recommended are
very strongly linked
to consumer needs
and preferences,
based on analysis of
survey results
Changes
recommended show
strong link (>75%) to
consumer needs and
preferences.
Changes
recommended
show sufficient
(>50%) link to
consumer needs
and preferences.
Changes
recommended
show little
(>25%) link.
Changes
recommended do
not meet consumer
needs and
preferences = 1;
Failure to link any
ideas for product
design = 0
5 4 3 2 0 - 1
7. Learning Objectives
OOrganise and compile survey findings
for market analysis.
ODraw sound and valid conclusions and
insights from compiled survey findings
OPropose improvements to product(s)
based on survey analysis
8. What is Survey Analysis?
8
Simply put, it’s
really about
deriving
MEANINGFUL
information from
the data collected
10. What are you searching for?
(1) looking for TRENDs?
(e.g. rise in childhood
obesity)
(2) BIG picture
comparison, patterns? etc
11. What are you searching for?
(4) Correlations
e.g. smoking vs. lung
cancer
(3) Checking for
similarities/ differences?
e.g. gender differences, age group
differences
A Girl’s best friend…
12. Consider this example…
You are conducting a market research to investigate the
receptiveness of a newly launched air freshner
100 respondents:
60 female, 40 male
13. Scenario A
O Out of 100
respondents, you
found out that
65% do not like
this scent.
100
80
60
40
20
0
65
35
Preference
Like Dislike
15. Scenario B
O However, as you delve
deeper into the data, you
realise that 25 out of 40
males like this scent.
O This makes up 62.5% of
the male sample
O Is your conclusion still the
same as scenario A?
O Why do you think that’s the
case?
Male Female
Dislike 15 50
Like 25 10
Total 40 60
17. Scenario C
Male Female
Dislike 15 50
Like 25 10
Female
Age 15-24 25-34 35-44 45-54
Dislike 2 18 20 10
Like 8 2 0 0
O Further analysis revealed that ONLY 10 out of the 60
females like the scent
OBUT the majority of this 10 (80%) are in the 15-24
age group
O How does this new information affect your overall
conclusion?
18. Mis/ Representation
OIs your analysis a fair and accurate
representation of the data?
OAll data and findings from scenarios A to C
are correct.
O But deeper analyses in scenarios B and C
surfaced a more accurate and fair
representation of the market research which
allowed for a more holistic conclusions
O Hence, we need to look deeper within the data
to surface interesting findings
19. Group Activity:
Analysis Practice
O Visit MeL and download a sample raw data file titled
“Lesson 5 Fanbrella Survey (Responses).xls”
O Analyse the data and come up with as much useful
information as possible
O Determine if there could have been some other data
collected which would have been more pertinent to your
analysis
Note: This survey was done by a previous group of 7INNOVA students
and scored an A grade
20. Notes on Filtering Data
O You will find that the data is already auto-filtered, meaning
to say, there are drop down menus for all the columns.
O To filter filter the data by age, click on drop-down menu for
Age and select either 15-20, 21-30, 41-50 or >51.
O To further filter the data e.g. by gender, click on drop down
menu for Gender and select either Female or Male.
O Using the above example for instance, after you filter first
by Gender, then by Age, you will find that there are 7
respondents who are above 40 and the majority of them
are females.
22. To clear all data filter to show all,
click Data FilterClear
22
23. 1. Are there questions that can answer the basic
question?
O e.g. What is the age of the majority of the respondents?
2. Go into specifics: Who are these people that say
that they never use an umbrella?
O i.e. What are their main reasons?
3. Try to go deeper:
O Of those who do carry umbrellas, what is their most
preferred method of carrying it? Is there a gender-specific
preference for any method?
24.
25. Let’s take a look at some possible
scenarios that can be inferred from the
sample data:
O24 of the 31 respondents (about 77%) who
have never used an umbrella in a week would
also not use “Fanbrella”.
OTheir reason being, both these products are
troublesome and a burden to carry about.
OMost who carry umbrellas choose to carry it in
a bag – a feature that needs to be incorporated
into any improvements that is made.
OThose who carry it in their hands are
predominantly males (7 out of 9 or about 78%)
27. Open-ended questions
O Open-ended questions such as “if willing, why?” can be
sorted into categories, e.g. time-saving.
O (As this is an open-ended question, it can’t be done by
filtering. Students need to categorize the answers
themselves.)
O Remember to clear the filter and show all data before
doing a new set of filtering.
O To clear all data filter to show all, click Data
FilterClear
28. Analysing Your Data
Using what you’ve learnt in class, analyse your
own survey data.
Use your analysis to see:
• How you can make your product more
appealing to your target consumer group
• What improvements should/ can be made to
your product.
29. Findings & Analysis
O Submit your survey
questions, tabulated findings/
implications, suggestions for
changes to product design in
either PowerPoint slides or as
a Word document.
(All raw data should also
be submitted to your tutor.)
29
30. Assessment 2: (15%)
Submit your print out with the following info :
Osurvey objectives and questions (from Google)
Oraw data (from Google)
Otabulated findings and graphs (from Google)
Osurvey findings and implications
Osuggestions for improvement
O final sketch
Due Date: Friday 28th November 5pm to my
pigeon hole 30
7INNOVA
31. Magnetic Earrings
Product
2 pierced earrings that are
made of silver with a magnet on
the base.
There are also 12 coloured
Suggested Unique Selling Points
O assemble and reconfigure the design of
earrings by yourself to suit your
reference, outfits and moods
O The metal dots are light enough that they
generally won’t come loose and fall off in
everyday wear
31
Taken from http://bit.ly/ADnMI0
metal dots
Cost Price = S$55
32. Glo Pillow
Unique Selling Points
O 40 minutes before the pre-set alarm time
the pillow begins to glow and gently
brings the user out of sleep.
O This natural waking process helps to set
the circadian rhythm or "body clock" and
results in more healthy sleep/wake
patterns.
32
Product
The Glo pillow is an alternative to the
traditional alarm clock. The pillow uses an LED
fabric substrate below the surface to wake the
user using light. This substrate also functions
as an optional display, showing the time on the
pillows surface using the grid of LEDs below.
Cost Price = S$45
Taken from http://bit.ly/pEpkOR
33. BreadWrite
33
Suggested Unique Selling Points
O The message gets “toasted” into the
toast itself and gives new meaning to
“read while you eat”.
O Add personalised messages,
reminders etc. to your toast.
Product
This toaster incorporates a little message
board where one can write quick notes.
Cost Price: S$128
Taken from http://bit.ly/19Ugou
34. Cool Ice Straw Tray
Product
The Ice Straw Tray comes with four reusable
straws that can be frozen in water, juice, or
cola. After the ice melts, the straws become
exposed.
34
Suggested Unique Selling Points
O Simple to use - fill, freeze, serve
O 3-in-1: Straw, Stirrer and Ice
O Impress your guest, straws add zing to any
occasion such as birthday parties, gatherings
or kids' parties
O Re-usable!
Taken from http://bit.ly/ocz119
Cost Price = S$4
35. Color My Shower
Product
A high quality shower head with built-in LED lights
that changes its color according to water
temperature: Green (< 32C), Blue (32-41C), Red
(41-45C), Red Flashes (> 45C).
35
Suggested Unique Selling Points
O No batteries or external power supply needed.
The LED lights in the shower head are powered
by the water current
O Light can be turned on/off as you like by pressing
a button.
O Water Saving: Restricts the amount of water
flowing.
Taken from http://bit.ly/yvvwi4
Cost Price = S$12
36. Virtual
Keyboard
36
Suggested Unique Selling Points
O Small cube projector slight bigger than
the size of a lighter.
O Smoothly connects to your mobile
devices (tablet pcs, notebooks,
smartphones etc.) and desktop pc.
O Full-size keyboard and producing real
tapping sounds.
Taken from http://bit.ly/mP4MMy
Product
A light projected keyboard based on
an optical recognition mechanism
technology that enable the user to tap
on the projected key images.
Cost Price = S$110
Editor's Notes
Tutor might want to let class voice out opinions, and conclude that this perfume seems to appeal more to men than women. Could it be due to the scent or the packaging?
The company can then conduct further studies with MEN to investigate the cause. If these men are drawn to the scent, then it could be re-launched as a men’s perfume. If they are drawn to the packaging, then maybe the company can come up with a series of interesting packaging design.
Tutor might want let class voice out opinions and conclude that this perfume seems to appeal more to younger women among the females.
Maybe the company can launch another survey targeted at younger ladies. And if the final findings reveal that younger women indeed like this perfume, then the company can start targeting all marketing efforts towards younger women. Contrary to scenario A, this product now has a huge potential to be a success, which may be a very different conclusion in comparison.
Tutors to give a short tutorial, if needed, on data filtering in Google or in Excel.
Tell students to submit 2 working days after the lesson
Tell students to submit 2 working days after the lesson