The document outlines different decision making techniques for evaluating options for a restaurant project, including ranking alternatives, pairwise comparisons, grid analysis, and the Analytic Hierarchy Process. It discusses measuring various effects of the project using different scales of measurement and evaluating options through group work activities like defining key effects, proposing an evaluation method and scale, and discussing results. The document provides guidance on tools and processes for assessing and selecting between alternatives for the restaurant project.
The power point presentation is about SPSS Software. It shows how to enter the data and to upload the data from external sources into SPSS. The presntation also shows how to save the files in excel form and in .sav form.
управление технологической структурой производстваЛана Ратнер
Переход на новые технологии, эффективность которых еще не до конца ясна, рискованный шаг для любой компании. Даже для крупного энергетического концерна. Какая стратегия инвестирования в новые технологии будет оправдана, в том случае, если старые уже достигли своего технологического предела, но дают стабильный доход, а новые только на пути между нижним и верхним порогами рентабельности?
Давно доказано, что сотрудничество в инновационной деятельности просто необходимо. Сотрудничество позволяет генерировать более интересные идеи, оно же позволяет их эффективно воплощать, соединяя комплиментарные ресурсы партнеров. Однако на практике далеко не так все гладко. Какие же барьеры встречаются на пути сотрудничества? Как их оценивают представители различных компонент региональной инновационной инфраструктуры? О чем это говорит?
The power point presentation is about SPSS Software. It shows how to enter the data and to upload the data from external sources into SPSS. The presntation also shows how to save the files in excel form and in .sav form.
управление технологической структурой производстваЛана Ратнер
Переход на новые технологии, эффективность которых еще не до конца ясна, рискованный шаг для любой компании. Даже для крупного энергетического концерна. Какая стратегия инвестирования в новые технологии будет оправдана, в том случае, если старые уже достигли своего технологического предела, но дают стабильный доход, а новые только на пути между нижним и верхним порогами рентабельности?
Давно доказано, что сотрудничество в инновационной деятельности просто необходимо. Сотрудничество позволяет генерировать более интересные идеи, оно же позволяет их эффективно воплощать, соединяя комплиментарные ресурсы партнеров. Однако на практике далеко не так все гладко. Какие же барьеры встречаются на пути сотрудничества? Как их оценивают представители различных компонент региональной инновационной инфраструктуры? О чем это говорит?
HUDE 225Take Home Directions You are a psychologist working a.docxwellesleyterresa
HUDE 225
Take Home
Directions: You are a psychologist working at a local high-school, and the principal wants to create a pre-assessment of 9th grade students’ algebra ability, in order to identify those in need of remedial instruction.
A team of math teachers constructs the test, and pilots it with one class of students. After these data are collected, the principal asks you to perform an item analysis, in order to provide information about the suitability of the test.
Below is item-response data for 10 participants on 5 selected-response items from the test. All of these items are dichotomous and each are designed to tap the same ability: algebra. Additionally, all of the items feature four possible answer choices.
Your task is to compute all relevant CTT and IRT statistics that we have learned in classfor these particular items. You may use all course materials, and any computer programs (e.g., Excel, SPSS, JMP) or a hand calculator to assist you. Round your answers to two decimal places.
Also—you are the only psychologist in this particular school, so please do your own work. This activity is worth a total of 70 points.
Data:
Examinee
Items
Score
1
2
3
4
5
1
1
1
1
1
1
5
2
1
1
1
0
1
4
3
1
1
1
1
1
5
4
0
0
0
0
0
0
5
1
1
0
1
1
4
6
0
0
0
0
1
1
7
0
1
0
0
0
1
8
1
1
1
1
1
5
9
0
0
1
0
0
1
10
1
0
0
0
0
1
P (5 points)
Q (5 points)
Variance (5 points)
Standard deviation
(5points)
D (5 points)
Point-biserial correlation
(5 points)
Inter-Item Covariance Matrix (5 points: .5 point per covariance)
Item Number
1
2
3
4
5
1
2
3
4
5
Inter-Item Correlation Matrix (5points: .5 point per correlation)
Item Number
1
2
3
4
5
1
1
2
1
3
1
4
1
5
1
Test Statistics (6 points)
Average Score
Composite Variance
Composite SD
Cronbach’s Alpha
Standard Error of Measurement
Standard Error of Estimate
Item-Characteristic Curves (Paste below, 5 points):
(Note: Because of the small sample-size, your principal is only requiring a 1pl IRT model)
Test Information Function (Paste below- 1 point):
Item difficulty parameters (5 points):
Item
b
1
2
3
4
5
Item-Analysis Report: Based on the results of your item analysis, do you think this test is suitable for the purpose for which it was designed? Are there any possible revisions you might recommend? Explain your answer using relevant statistics you calculated above as support. Remember, students may be placed in remedial algebra based on their score on this test, so your report is important. (13 points).
Classical Test Theory and
Item Analysis
1
Review: Why do we measure?
In psychology and education, the
abilities and traits we are interested
in cannot be directly observed
Knowledge, cognitive skills, attitudes,
personality, etc.
So, we use measures to indirectly
assess students on these variables
2
A Classic Discovery
In 1904, Charles Spearman posited the following equation:
X = T ...
HUDE 225Take Home Directions You are a psychologist working a.docxwellesleyterresa
HUDE 225
Take Home
Directions: You are a psychologist working at a local high-school, and the principal wants to create a pre-assessment of 9th grade students’ algebra ability, in order to identify those in need of remedial instruction.
A team of math teachers constructs the test, and pilots it with one class of students. After these data are collected, the principal asks you to perform an item analysis, in order to provide information about the suitability of the test.
Below is item-response data for 10 participants on 5 selected-response items from the test. All of these items are dichotomous and each are designed to tap the same ability: algebra. Additionally, all of the items feature four possible answer choices.
Your task is to compute all relevant CTT and IRT statistics that we have learned in classfor these particular items. You may use all course materials, and any computer programs (e.g., Excel, SPSS, JMP) or a hand calculator to assist you. Round your answers to two decimal places.
Also—you are the only psychologist in this particular school, so please do your own work. This activity is worth a total of 70 points.
Data:
Examinee
Items
Score
1
2
3
4
5
1
1
1
1
1
1
5
2
1
1
1
0
1
4
3
1
1
1
1
1
5
4
0
0
0
0
0
0
5
1
1
0
1
1
4
6
0
0
0
0
1
1
7
0
1
0
0
0
1
8
1
1
1
1
1
5
9
0
0
1
0
0
1
10
1
0
0
0
0
1
P (5 points)
Q (5 points)
Variance (5 points)
Standard deviation
(5points)
D (5 points)
Point-biserial correlation
(5 points)
Inter-Item Covariance Matrix (5 points: .5 point per covariance)
Item Number
1
2
3
4
5
1
2
3
4
5
Inter-Item Correlation Matrix (5points: .5 point per correlation)
Item Number
1
2
3
4
5
1
1
2
1
3
1
4
1
5
1
Test Statistics (6 points)
Average Score
Composite Variance
Composite SD
Cronbach’s Alpha
Standard Error of Measurement
Standard Error of Estimate
Item-Characteristic Curves (Paste below, 5 points):
(Note: Because of the small sample-size, your principal is only requiring a 1pl IRT model)
Test Information Function (Paste below- 1 point):
Item difficulty parameters (5 points):
Item
b
1
2
3
4
5
Item-Analysis Report: Based on the results of your item analysis, do you think this test is suitable for the purpose for which it was designed? Are there any possible revisions you might recommend? Explain your answer using relevant statistics you calculated above as support. Remember, students may be placed in remedial algebra based on their score on this test, so your report is important. (13 points).
Classical Test Theory and
Item Analysis
1
Review: Why do we measure?
In psychology and education, the
abilities and traits we are interested
in cannot be directly observed
Knowledge, cognitive skills, attitudes,
personality, etc.
So, we use measures to indirectly
assess students on these variables
2
A Classic Discovery
In 1904, Charles Spearman posited the following equation:
X = T ...
A primer in Data Analysis. To substantiate the concepts, I presented Python code in the form of an ipython notebook (not included - get in touch for these, email and twitter are on the last slide).
The talk starts by describing general data analysis (and skills required). I then speak about computing descriptive statistics and explain the details of two types of predictive models (simple linear regression and naive Bayes classifiers). We build examples using both predictive models using python (Pandas and Matplotlib).
Decision Trees - The Machine Learning Magic UnveiledLuca Zavarella
Often a Machine Learning algorithm is seen as one of those magical weapons capable of revealing possible future scenarios to whoever holds it. In truth, it's a direct application of mathematical and statistical concepts, which sometimes generate complex models to be interpreted as output. However, there are predictive models based on decision trees that are really simple to understand. In this slide deck I'll explain what is behind a predictive model of this type.
Here the demo files: https://goo.gl/K6dgWC
5. Product
• The main service of my project it:
- cooking and serving regional Polish food.
CUSTOMERS
Potential clients in my restaurant:
• Official:
- Gender: male
- Age: 40 years old
- Geography: Lublin, Poland
- Income level: 7000zł
- His opinion: „Finally, I can eat a good lunch break.”
6. Customers
• Student:
- Gender: female
- Age: 22 years old
- Geography: Lublin, Poland
- Income level: 600zł
- His opinion: „Eating like at grandma's house. Finally, something other than fast
foods.”
• Tourist:
- Gender: female
- Age: 33 years old
- Geography: Paris, France
- Income level: 3000 EUR
- Her opinion: „Cuisine differs from the French but very good.”
7. Customers
• Pensioner:
- Gender: male
- Age:70 years old
- Geography: Zamość, Poland
- income level: 2500zł
- His opinion:”It was nice to go back to the old tastes.”
• Schoolboy:
- Gender: male
- Age:13 years old
- Geography: Wrocław, Poland
- Income level: 0zł
- His opinion: „Here is boring. Missing fast foods and cola”
8. Home work for Monday
• Finish your research!!!
• Find 5 opinions
• Describe people and their opinions
10. Decision Making Techniques:
Choosing Between Options
• Ranking
• Pairwise Comparisons
• Grid Analysis
• The Analytic Hierarchy Process (AHP)
11. Ranking
• The procedure for ordering items in ascending
(descending) preference for one or more selected
indicators to compare
• In the case of strict ranking is not allowed to point to
elements of the equivalence
• With a non-strict ranking multiple elements can
occupy the same place in the ranking and receive the
same rank
• This method is used when the number of options
n≤7±2
12. Choose the trip of your dream
By ranking
By pairwise comparisons
By grid analysis
Is there any difference?
You conclusions….
13. Pairwise Comparisons
• The procedure of determination of the preferences
by comparing all possible pairs of objects (options)
• Results of the comparison of pairs of objects
represented as a matrix
• Rank is calculating by summation of numerical
representations for paired comparisons for each
option
• If the comparison is made on various parameters or
group of experts, for each indicator or expert the
matrix of pairwise comparisons is preparing
14. Some possible types of numerical presentation
1, if ai a j , ai ≈ a j
xij =
0 , if ai a j
1, if ai a j , 2 , if ai a j ,
xij = 0.5, if ai ≈ a j xij = 1, if ai ≈ a j
0 , if ai a j 0 , if ai a j
15. Example of results of paired comparisons on a set of
five alternatives
Options 1 2 3 4 5 ∑x
j
ij Rank
1 - 0.5 0 1 1 2.5 2
2 0.5 - 1 0.5 1 3 1
3 1 0 - 0 1 2 3
4 0 0.5 1 - 0 1.5 4
5 0 0 0 1 - 1 5
16. Median comparison
• Any two elements of the set of alternatives
are selected and ordered
• The third element is compared with the best
of the first two, and if it is worse, with the
worst, and so one find its place
• The fourth element is compared first to the
median to determine left or right semi-set to
further refine the location of the fourth
element, etc.
17. Grid Analysis
• a number of good alternatives to choose from
• many different factors to take into account
?????
• list your options as rows on a table, and the factors
you need consider as columns
• score each option/factor combination, weight this
score by the relative importance of the factor,
• add these scores up to give an overall score for each
option
26. Effects of the project
• Commercial
• Social
• Ecological
• Budgetary/economical
• ………..
27. How we can estimate the effect?
• measurement is the assignment of numbers
to objects
• direct and indirect measurements
• what to measure, how to measure
28. Scale of measurement
Formally, the scale is a set of three elements
<X,Φ,Y>, where
•X – real object
•Y – number
•Φ- mapping X on Y
29. Nominal Scale
• Simply labels objects
• Categorical data are measured on
nominal scales which merely assign
labels to distinguish categories
30. Ordinal Scale
• Numbers are used to place objects in order
• But, there is no information regarding the
differences (intervals) between points on the
scale
31. Interval Scale
• An interval scale is a scale on which equal
intervals between objects, represent equal
differences
• The interval differences are meaningful
• But, we can’t defend ratio relationships
• For example, the difference between 10 and 20
degrees is the same as between 80 and 90 degrees.
But, we can’t say that 80 degrees is twice as hot as
40 degrees. There is no ‘true’ zero, only an ‘arbitrary’
zero
32. Ratio Scale
• Have a true zero point
• Ratios are meaningful
• Physical scales of time, length and
volume are ratio scales
33.
34. Group work
Define the main effects of your projects
(15 min)
Propose a method and a scale to evaluate
the effects (15 min)
Discuss your results (5 min)