Presentation by Jacob van Etten.
CCAFS workshop titled "Using Climate Scenarios and Analogues for Designing Adaptation Strategies in Agriculture," 19-23 September in Kathmandu, Nepal.
Presentation by Jacob van Etten.
CCAFS workshop titled "Using Climate Scenarios and Analogues for Designing Adaptation Strategies in Agriculture," 19-23 September in Kathmandu, Nepal.
If you recognize yourself in this description, please take 5 minutes to read on and answer these 3 simple questions:
"By now you have been working for several years with Excel, gradually getting better at it and making simple or elaborate spreadsheets for private or business use. All in all, you are quite satisfied with your work and the results."
Cover PageComplete and copy the following to Word for your cover p.docxfaithxdunce63732
Cover PageComplete and copy the following to Word for your cover page. Be sure that the document is stapled properly. Do not use a plastic cover or folder.In the Footer of the Word documents, add the Now() function to show what day and time the documents were printed.Submit the Excel file to CANVAS as: lastname_firstname.xls. Hand-in the Word document immediately prior to Exam 1.Although students are encouraged to ask questions for clarification, this exercise is intended to be well within the capability of students at the 3000 level and studentsshould be able to complete the project with minimal assistance. Instructions are included on each worksheet but feel free to request clarification.ACG 3401 Accounting Information SystemsExcel AssignmentSubmitted By:Name Last: First:<-- Only use this for cover page.Spring 2015By submitting this document, I affirm that the work is the product of my own efforts withoutthe assistance of another person and that I have not given assistance to another student.<-- You must sign for the submission to be graded.Signature of student
InstructionsINSTRUCTIONS:This is an .xls file and should not be changed to another filetype in order to preserve macros.Follow the instructions on each worksheet. Copy results to MS Word and include pages numbers.The page numbers for each exercise are given below (at bottom of this worksheet).Appearance counts. Be sure that results are presented professionally and are readable.Three worksheets are data files and are referenced in the instructions. These are named Product Data, Industry Data, and Data Worksheet.Create range names for the following:Remember ranges should not include the headers (field names). Be careful to insure you have selected the entire range for that field.(Click F3 to view the range names - click these to insert to formula or you can type them in directly.)You may need to create range names other than these.From the Industry Data Worksheet, create range names for the following:1) Employees2) Sales3) Address4) Name5) State6) ZIPFrom the Data Worksheet, create range names for the following:1) Cash2) Company3) EBIT4) Eff_Tax_Rate5) Exchange6) SICCreate a range name for the entire Product Data table but include the headers. I used the name 'Product'.Tab ColorsGreenDatabases to be used.YellowExamplesBlueInstructions to perform graded exercisesWhen copying portions of the worksheet to your MS Word document, you will find the "Snipping Tool" very helpful.Checklist for Submitted Documents (Be sure that all documents are formatted properly and readable)Page No.naCover page with name and section number (stapled)ResultsFormulas1Horizontal and Vertical AnalysisYesYes2Financial Ratio Analysis - Results and Formulas.YesYes3VlookupYesYes3HLookupYesYes4DataTableYesYes4DropDown Box - Result Only.YesNo5Dfunctions - Results and Formulas.YesYes6Functions1YesYes7Functions2YesYes8Annual Income StatementYesYes9Macro.
Program 1 – CS 344This assignment asks you to write a bash.docxwkyra78
Program 1 – CS 344
This assignment asks you to write a bash shell script to compute statistics. The purpose
is to get you familiar with the Unix shell, shell programming, Unix utilities, standard
input, output, and error, pipelines, process ids, exit values, and signals.
What you’re going to submit is your script, called stats.
Overview
NOTE: For this assignment, make sure that you are using Bash as your shell (on Linux,
/bin/sh is Bash, but on other Unix O/S, it is not). This is because the Solaris version of
Bourne shell has some annoying bugs that are really brought out by this script. Bash can
execute any /bin/sh script.
In this assignment you will write a Bourne shell script to calculate averages and medians
from an input file of numbers. This is the sort of calculation I might do when figuring
out the grades for this course. The input file will have whole number values separated by
tabs, and each line of this file will have the same number of values. (For example, each
row might be the scores of a student on assignments.) Your script should be able to
calculate the average and median across the rows (like I might do to calculate an
individual student's course grade) or down the columns (like I might do to find the
average score on an assignment).
You will probably need commands like these, so please read up on them: sh, read, expr,
cut, head, tail, wc, and sort.
Your script will be called stats. The general format of the stats command is
stats {-rows|-cols} [input_file]
Note that when things are in curly braces separated by a vertical bar, it means you should
choose one of the things; here for example, you must choose either -rows or -cols. The
option -rows calculates the average and median across the rows; the option -cols
calculates the average and median down the columns. When things are in square braces
it means they are optional; you can include them or not, as you choose. If you specify an
input_file the data is read from that file; otherwise, it is read from standard input.
Here is a sample run of what your script might return, using an input file called test_file
(this particular one can be downloaded here , note that in Windows, the newline
characters may not display as newlines. Move this to your UNIX account, without
opening and saving it in Windows, and then cat it out: you'll see the newlines there):
% cat test_file
1 1 1 1 1
9 3 4 5 5
6 7 8 9 7
3 6 8 9 1
3 4 2 1 4
6 4 4 7 7
% stats -rows test_file
Average Median
1 1
5 5
7 7
5 6
3 3
6 6
% cat test_file | stats –c
Averages:
5 4 5 5 4
Medians:
6 4 4 7 5
% echo $?
0
% stats
Usage: stats {-rows|-cols} [file]
% stats -r test_file nya-nya-nya
Usage: stats {-rows|-cols} [file]
% stats -both test_file
Usage: stats {-rows|-cols} [file]
% chmod -r test_file
% stats -columns test_file
stats: cannot read test_file
% stats -columns no_such_file
stats: cannot read no_such_file
% echo $?
1
Specifications
You must ch ...
If you recognize yourself in this description, please take 5 minutes to read on and answer these 3 simple questions:
"By now you have been working for several years with Excel, gradually getting better at it and making simple or elaborate spreadsheets for private or business use. All in all, you are quite satisfied with your work and the results."
Cover PageComplete and copy the following to Word for your cover p.docxfaithxdunce63732
Cover PageComplete and copy the following to Word for your cover page. Be sure that the document is stapled properly. Do not use a plastic cover or folder.In the Footer of the Word documents, add the Now() function to show what day and time the documents were printed.Submit the Excel file to CANVAS as: lastname_firstname.xls. Hand-in the Word document immediately prior to Exam 1.Although students are encouraged to ask questions for clarification, this exercise is intended to be well within the capability of students at the 3000 level and studentsshould be able to complete the project with minimal assistance. Instructions are included on each worksheet but feel free to request clarification.ACG 3401 Accounting Information SystemsExcel AssignmentSubmitted By:Name Last: First:<-- Only use this for cover page.Spring 2015By submitting this document, I affirm that the work is the product of my own efforts withoutthe assistance of another person and that I have not given assistance to another student.<-- You must sign for the submission to be graded.Signature of student
InstructionsINSTRUCTIONS:This is an .xls file and should not be changed to another filetype in order to preserve macros.Follow the instructions on each worksheet. Copy results to MS Word and include pages numbers.The page numbers for each exercise are given below (at bottom of this worksheet).Appearance counts. Be sure that results are presented professionally and are readable.Three worksheets are data files and are referenced in the instructions. These are named Product Data, Industry Data, and Data Worksheet.Create range names for the following:Remember ranges should not include the headers (field names). Be careful to insure you have selected the entire range for that field.(Click F3 to view the range names - click these to insert to formula or you can type them in directly.)You may need to create range names other than these.From the Industry Data Worksheet, create range names for the following:1) Employees2) Sales3) Address4) Name5) State6) ZIPFrom the Data Worksheet, create range names for the following:1) Cash2) Company3) EBIT4) Eff_Tax_Rate5) Exchange6) SICCreate a range name for the entire Product Data table but include the headers. I used the name 'Product'.Tab ColorsGreenDatabases to be used.YellowExamplesBlueInstructions to perform graded exercisesWhen copying portions of the worksheet to your MS Word document, you will find the "Snipping Tool" very helpful.Checklist for Submitted Documents (Be sure that all documents are formatted properly and readable)Page No.naCover page with name and section number (stapled)ResultsFormulas1Horizontal and Vertical AnalysisYesYes2Financial Ratio Analysis - Results and Formulas.YesYes3VlookupYesYes3HLookupYesYes4DataTableYesYes4DropDown Box - Result Only.YesNo5Dfunctions - Results and Formulas.YesYes6Functions1YesYes7Functions2YesYes8Annual Income StatementYesYes9Macro.
Program 1 – CS 344This assignment asks you to write a bash.docxwkyra78
Program 1 – CS 344
This assignment asks you to write a bash shell script to compute statistics. The purpose
is to get you familiar with the Unix shell, shell programming, Unix utilities, standard
input, output, and error, pipelines, process ids, exit values, and signals.
What you’re going to submit is your script, called stats.
Overview
NOTE: For this assignment, make sure that you are using Bash as your shell (on Linux,
/bin/sh is Bash, but on other Unix O/S, it is not). This is because the Solaris version of
Bourne shell has some annoying bugs that are really brought out by this script. Bash can
execute any /bin/sh script.
In this assignment you will write a Bourne shell script to calculate averages and medians
from an input file of numbers. This is the sort of calculation I might do when figuring
out the grades for this course. The input file will have whole number values separated by
tabs, and each line of this file will have the same number of values. (For example, each
row might be the scores of a student on assignments.) Your script should be able to
calculate the average and median across the rows (like I might do to calculate an
individual student's course grade) or down the columns (like I might do to find the
average score on an assignment).
You will probably need commands like these, so please read up on them: sh, read, expr,
cut, head, tail, wc, and sort.
Your script will be called stats. The general format of the stats command is
stats {-rows|-cols} [input_file]
Note that when things are in curly braces separated by a vertical bar, it means you should
choose one of the things; here for example, you must choose either -rows or -cols. The
option -rows calculates the average and median across the rows; the option -cols
calculates the average and median down the columns. When things are in square braces
it means they are optional; you can include them or not, as you choose. If you specify an
input_file the data is read from that file; otherwise, it is read from standard input.
Here is a sample run of what your script might return, using an input file called test_file
(this particular one can be downloaded here , note that in Windows, the newline
characters may not display as newlines. Move this to your UNIX account, without
opening and saving it in Windows, and then cat it out: you'll see the newlines there):
% cat test_file
1 1 1 1 1
9 3 4 5 5
6 7 8 9 7
3 6 8 9 1
3 4 2 1 4
6 4 4 7 7
% stats -rows test_file
Average Median
1 1
5 5
7 7
5 6
3 3
6 6
% cat test_file | stats –c
Averages:
5 4 5 5 4
Medians:
6 4 4 7 5
% echo $?
0
% stats
Usage: stats {-rows|-cols} [file]
% stats -r test_file nya-nya-nya
Usage: stats {-rows|-cols} [file]
% stats -both test_file
Usage: stats {-rows|-cols} [file]
% chmod -r test_file
% stats -columns test_file
stats: cannot read test_file
% stats -columns no_such_file
stats: cannot read no_such_file
% echo $?
1
Specifications
You must ch ...
New folderCSE2AIF 2015 Assignment 2.pdfCSE2AIF - Artifi.docxhenrymartin15260
New folder/CSE2AIF 2015 Assignment 2.pdf
CSE2AIF - Artificial Intelligence Fundamentals
2015 Individual Assignment 2
Due Friday 9 October 2015, 10:00am
General Information
This assignment is to be done individually, and contributes 20% of your final mark for this subject. The
submission date for the assignment is Friday 9th October 10:00am. Submission is both hardcopy AND
electronic. Details of what to submit are provided below. Make sure that you follow the directions carefully
and that the files are named exactly as specified in the instructions.
The assignment is to be done individually. This means that any code that you write must be your own. You
must not collude with other students in any way, and you must not outsource your work to any third party.
For information on plagiarism, see the La Trobe University policy on academic misconduct at
http://www.latrobe.edu.au/students/learning/academic-integrity. Plagiarism is treated very seriously.
Penalties will be applied and are strictly imposed.
Late Submission Policy
Penalties are applied to late assignments (5% of total possible marks for that task is deducted per day,
accepted up to 5 days after the due date only). An assignment submitted more than five working days after
the due date will not be accepted. Delays caused by computer downtime cannot be accepted as a valid reason
for a late submission without penalty. You must plan your work to allow for both scheduled and
unscheduled downtime.
Extension Policy
In order to apply for an extension of time to submit your assessment task, you must:
1. Complete the light brown sections of the ‘Request for an Extension of Time to Submit an Assessment
Task” form, which will be available from the subject’s LMS website
2. Submit the completed form to the Subject Coordinator with relevant supporting information (e.g.
medical certificate) either by email or in hard copy
3. The submission must be made three days or more before the original due date for the assessment task.
If it is less than three days before the due date, or after the due date, you should use the Special
Consideration process. You have up to three days after the due date to apply for special consideration. You
are not automatically granted an extension of time if you submit the form. The Subject Coordinator will
return this form to you (as a scan via email) with approval or rejection of your request clearly indicated. If
you are granted an extension of time, you should submit a copy of the approved form (showing the approval
and the new submission date) with your completed assessment task. The University’s Late Submission
penalties apply from the original submission date if your request for an extension is rejected, and from the
new submission date (provided on the approved form) if your request is accepted. Applications for extension
made because of poor time management are generally not accepted. You may wish to.
HW2.pdfCSEEEE 230 Computer Organization and Assembly La.docxadampcarr67227
HW2.pdf
CSE/EEE 230 Computer Organization and Assembly Language Homework 2 :: 50 pts
1 Instructions
You may work in pairs with a partner on this assignment if you wish or you may work alone. If you work with a partner,
only submit one zip archive with both of your names in the PDF document and source code file; you will each earn the
same number of points. Your zip archive must be uploaded to Blackboard by the assignment deadline. Section 3 describes
what to submit and by when.
2 Exercises
1. A MIPS word is stored at memory address 0x1000_100A. Is this word naturally aligned? If so, explain why, and if
not, explain why not.
2. Consider this C code. Assume the values of variables e, f, g, and h have been loaded from memory into registers $t0,
$t1, $t2, and $t3, respectively. Assume we are associating variable i with register $s0. Write the MIPS instructions—
not a complete program—that implements the assignment statement.
int e, f, g, h, i;
i = e * (f + g - h);
3. (a) Explain why we cannot write addi $t0, $zero, 65536 to load the immediate 65,536 into $t0. (b) Write a single
lui instruction that loads the immediate 65,536 into $t0.
4. Many processor ISA's have instructions which rotate the bits of a word left or right. During a rotate left operation,
bits that would normally be lost during a shift left are instead rotated into the least significant bits. For example,
suppose $t0 contains 0x9122_3344 and we rotate $t0 left n bit positions,
$t0 before rotate left: 1001 0001 0010 0010 0011 0011 0100 0100
$t0 after rotate left 1 bit position: 0010 0010 0100 0100 0110 0110 1000 1001
$t0 before rotate left: 1001 0001 0010 0010 0011 0011 0100 0100
$t0 after rotate left 7 bit positions: 1001 0001 0001 1001 1010 0010 0100 1000
A rotate right works similarly, except bits that would normally be lost during a shift right are rotated into the most
significant bits. MIPS does not have rotate left or rotate right instructions. However, they can be implemented as
pseudoinstructions. For this exercise, write the MIPS physical instruction sequence which would implement a pseudo -
instruction rotl1 $dst, $src (rotate left by 1) that rotates the bits in $src one position to the left and writes the
result to $dst. You are only allowed to use three registers in your code: $src, $dst, and $at; $src shall not be modified.
Note, $src and $dst are not real MIPS registers, but rather, are placeholders for the registers that are actually used
when writing the rotl1 instruction. For example, if the programmer writes rotl $t0, $t1 then $src is $t1 and $dst
is $t0. I'll give you a hint, these are your instructions, which I wrote in this order: srl, sll, or.
5. Write MIPS assembly language code that would define and initialize these variables in the .data section.
int e = 0 , f = 10, g = -1;
char ch = ' ';
char char_array[128] = { '\0' };
int int_array1[100] = { 0 };
int int_array2[3] = { 1, 2, 3 };
6. Write assembly language instructions—not a complete pro.
FOR MORE CLASSES VISIT
www.cis336.com
CIS 336 Final Exam
Question 1. 1. (TCO 1) A DBMS performs several important functions that guarantee the integrity and consistency of the data in the database. Which of the following is NOT one of those functions?
In Section 1 on the Data page, complete each column of the spreads.docxsleeperharwell
In Section 1 on the Data page, complete each column of the spreadsheet to arrive at the desired calculations. Use Excel formulas to demonstrate that you can perform the calculations in Excel. Remember, a cell address is the combination of a column and a row. For example, C11 refers to Column C, Row 11 in a spreadsheet.
Reminder: Occasionally in Excel, you will create an unintentional circular reference. This means that within a formula in a cell, you directly or indirectly referred to (back to) the cell. For example, while entering a formula in A3, you enter =A1+A2+A3. This is not correct and will result in an error. Excel allows you to remove or allow these references.
Hint: Another helpful feature in Excel is Paste Special. Mastering this feature allows you to copy and paste all elements of a cell, or just select elements like the formula, the value or the formatting.
"Names" are a way to define cells and ranges in your spreadsheet and can be used in formulas. For review and refresh, see the resources for Create Complex Formulas and Work with Functions.
Ready to Begin?
1. To calculate
hourly rate, you will use the annual hourly rate already computed in Excel, which is 2080. This is the number most often used in annual salary calculations based on full time, 40 hours per week, 52 weeks per year. In E11 (or the first cell in the
Hrly Rate column), create a formula that calculates the hourly rate for each employee by referencing the employee’s salary in Column D, divided by the value of annual hours, 2080. To do this, you will create a simple formula:
=D11/2080. Complete the calculations for the remainder of Column E. If you don’t want to do this cell by cell, you can create a new formula that will let you use that same formula all the way to the end of the column. It would look like this:
=$D$11:$D$382/2080.
2. In Column F, calculate the
number of years worked for each employee by creating a formula that incorporates the date in cell F9 and demonstrates your understanding of relative and absolute cells in Excel. For this, you will need a formula that can compute absolute values to determine years of service. You could do this longhand, but it would take a long time. So, try the
YEARFRAC formula, which computes the number of years (and even rounds). Once you start the formula in Excel, the element will appear to guide you. You need to know the “ending” date (F9) and the hiring date (B11). The formula looks like this:
=YEARFRAC($F$9,B11), and the $ will repeat the formula calculation down the column as before if you grab the edge of the cell and drag it to the bottom of the column.
3. To determine if an employee is
vested or not In Column I, use an
IF statement to flag with a "Yes" any employees who have been employed 10 years or more. Here is how an IF statement works:
=IF(X is greater (or less th.
STAT-522 (Data Analysis Using R) by SOUMIQUE AHAMED.pdfSOUMIQUE AHAMED
STAT-522 (Data Analysis Using R) by SOUMIQUE AHAMED, Division of Agronomy, Faculty of Agriculture - Wadura, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir.
Building data fusion surrogate models for spacecraft aerodynamic problems wit...Shinwoo Jang
Abstract. This work concerns a construction of surrogate models for a specific aerodynamic data base. This data base is generally available from wind tunnel testing or from CFD aerodynamic simulations and contains aerodynamic coefficients for different flight conditions and configurations (such as Mach number, angle-of-attack, vehicle configuration angle) encountered over different space vehicles mission. The main peculiarity of aerodynamic data base is a specific design of
experiment which is a union of grids of low and high fidelity data with considerably different sizes. Universal algorithms can’t approximate accurately such significantly non-uniform data. In this work a fast and accurate algorithm was developed which takes into account different fidelity of the data and special design of experiments.
Case Study Analysis 2The Cholesterol.xls records cholesterol lev.docxwendolynhalbert
Case Study Analysis 2
The Cholesterol.xls records cholesterol level data for individuals. Descriptions for the data follow:
· Cholesterol: Cholesterol level (mg/dL)
· Income: annual income in $
· Age: age of individual
· Jogging: number of hours an individual spends on jogging a day
· Saturated fat: the amount of saturated fat an individual takes a day (g)
(A) Develop an estimated regression equation that can be used to predict Cholesterol level using age, jogging income, and saturated fat. Discuss your findings including interpretation of slope of each variable and significance, using at least 200 words. Use .
(B) Starting with the estimated regression equation developed in part (A), delete any independent variables that are not statistically significant and develop a new estimated regression equation that can be used to predict Cholesterol level. Use . Discuss your findings including interpretation of slope of each variable and significance, using at least 200 words. Use .
(C) Compare model (A) and (B) in terms of R^2 and which model fits the data better? Discuss this using at least 100 words
(D) In model B, what are the most important factors affecting Cholesterol level? What are the least important factors? Discuss this using at least 100 words
Assignment1DueTHURSDAY.zip
Assignment1/Assignment1-17.pdf
ICT209 Assignment 1, Murdoch University 2016
ICT209 Assignment 1, Murdoch University 2016 1
ICT209 Assignment 1 2016
Objectives:
• Demonstrate that you can do Object Oriented design
• Demonstrate that you can write Object Oriented programs using C++.
• Demonstrate that you can design and write programs using user defined data structures.
• Demonstrate that you can work with data files.
• Demonstrate that you can write test plans and show evidence of systematic testing.
• Demonstrate that you can design using UML.
You do not work in groups for this assignment, as this is an individual assignment.
Worth:
14% of the unit
Due:
Midnight (end of Session 7). This would be the 7th teaching week.
How to submit (also see unit guide - section on Assignment/Project submission/return):
Singapore or Dubai Campus:
Into the assignment submission area for the unit in LMS. Follow all directions from your lecturer.
Murdoch Campus Internal students:
Into the assignment submission area for the unit in LMS.
Externals:
Into the assignment submission area for the unit in LMS.
For submitting in LMS, zip up the entire folder. Make sure that you have included all needed files. Do not
include temporary files or files not relevant to the assignment.
Name the zip file with the unit code, Assignment number, your name, student number.
ICT209Asg1JoBlogs12345678.zip
or alternatively,
ICT209_Asg1_JoBlogs_12345678.zip
Textual submissions should be type-written. External documentation can only be in the following formats:
Text (.txt)
PDF (.pdf)
RTF (.rtf)
HTML (.html)
Image formats : PNG ...
Students should work individually on the Mid-Term Students are enco.docxorlandov3
Students should work individually on the Mid-Term: Students are encouraged to talk and show each other tricks in Excel, if helpful, but files should not be shared or copied, and all students should be able to replicate analysis they used for the Mid-Term.
Instructions: For each problem, first read the background in the problem and then refer to the related tab in “Mid-Term.xlsx” for the data to be used. Each student’s successfully completed Mid-Term will include:
(1) a Word doc with each section of the problem (e.g., Problem 1, part a, sub-part i) answered clearly and straightforwardly, including brief explanations in sentence form, charts pasted into the doc, references to the XLSX file, etc. (Please type answers and paste data/charts/etc. into this DOC and save as with “- [Last Name]” at the end).
(2) an Excel file showing the work, formulas, Pivot tables, charts, etc. used to calculate and analyze the data. (Please also use the original XLSX, manipulating data, adding tabs, etc. and save as with “- [Last Name]” at the end).
PART I – Problems: Answer in the same format (DOC/XLSX) used in the homework assignments.
1. (100 Points) Revenue Forecasting Application – Show work on TAB 1 (or add “1” at the beginning of other tabs used to answer this questions) on XLSX: As we discussed in class and as Silver notes in his book, a prediction of percentage chance of something happening is not the same as saying that thing will actually happen. Suppose, for example, that a local government would expect $100 million in tax revenue for its general fund in a “good” economy and $60 million during a “bad” economy. Suppose that every fiscal year there is a 15% chance (independent probability unrelated to the previous year) of a bad economy and an 85% chance of a “good” economy. Also suppose that the government cannot know whether it was a “good” or “bad” economy until the end of the fiscal year, well after the budget has been set.
a. Possible Outcomes: In this example, how many possible outcomes are there for each fiscal year? What are these outcomes? Are they mutually exclusive? Are they collectively exhaustive?
Answer:
There are two options that government can foresee and 2 outcomes that can really happen. Taking it into consideration we can conclude that total amount of possible outcomes is 4
b. Decision Tree: Create a decision tree to illustrate the possible outcomes of 4 fiscal years. You should show (i) the independent probability of each event (chance node), based on the information in the question, and (ii) the final amount of tax revenue after 4 years given these possible 4-trial outcomes (end nodes), but do not need to calculate the full probability of each 4-trial outcome at this point.
Answer: (Paste Graphic Here or Create it Using the “Insert” Ribbon in Word and Shapes)
c. Calculating the Probability of Outcomes over Multiple Trials: Determine the probability that this local government will face “good” economies 0, 1, 2, 3,.
Itm310 problem solving #7 complete solutions correct answers keySong Love
ITM310 - Problem Solving #7 complete solutions correct answers key
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Case study instructions director’s request for p cs complete solutions correc...Song Love
Case Study Instructions Director’s Request for PCs complete solutions correct answers key
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Tutorial 8 based on lectures 22 24 (tg) complete solutions correct answers keySong Love
Tutorial 8 based on lectures 22-24 (TG) complete solutions correct answers key
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Liberty university busi 313 quiz 4 complete solutions correct answers slideshareSong Love
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Liberty University BUSI 311 quiz 5 complete solutions correct answers slideshare
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Liberty University BUSI 311 quiz 4 complete solutions correct answers slideshare
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Liberty University BUSI 311 quiz 3 complete solutions correct answers slideshare
Five different versions
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1 3 my statlab module one problem set complete solutions correct answers keySong Love
1-3 MyStatLab Module One Problem Set complete solutions correct answers key
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Liberty University PSYC 101 quiz 14 solutions answers slideshare
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Liberty University PSYC 101 quiz 13 solutions answers slideshare
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Liberty University PSYC 101 quiz 12 solutions answers slideshare
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Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
1. Statistics 141 - Homework 6 complete solutions correct answers key
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Write a report showing the code, results and plots for the questions below.
Put a printed version in Charles Arnold's mailbox in the Statistics department o_ce,4th oor of
the Mathematical Sciences Building, and
send an electronic version to dtemplelang@ucdavis.edu with the subject STA141 Assignment 6.
Place the following text at the top of your report and sign it on the physical version you submit:
I certify that I have acknowledged any code that I used from any other person in the class, from
Piazza or any Web site or book or other source. Any other work is my own.
1 UNIX Shell Tools
In this part of the assignment, you will use UNIX shell tools to process data outside of R and also
to get data into R.
In the Data directory on the class Web site, there is a collection of CSV _les for the monthly airline
delay data from July 2012 to June 2013, inclusive. This is a compressed tar _le Airline2012_13.tar.gz.
Within this archive, each _le name is of the form year_Month.csv,e.g. 2013_January.csv.
Download this _le and extract the _les into a single directory. Use a shell command not a point-
and-click GUI (graphical user interface).
We want to count the number of ights for the 5 airports OAK,SFO, SMF, LAX and JFK. The
tasks are simple to state.
i) Compute the number of outbound ights for each of the _ve airports OAK,SMF, LAX, SFO
and JFK, and sort these counts from largest to smallest.
Perform the same computations in R. Compare the total time for each approach.
ii) Compute the total number of ights in and out of the _ve airports, i.e., the sume of both the
inbound and outbound ights. You can do this however you want using a mix of the shell and R
code. One way is to _rst obtain the lines in the _les which involve any of these _ve airports. Then
obtain a count for each pair of airports, i.e., ORIGIN, DESTINATION pairs. At most, how many
will there be? Then read these counts by ORIGIN, DESTINATION pairs into R and compute the
total number of ights for each of the 5 airports.
Use only the UNIXshell tools to do i). For ii), use the shell tools to greatly reduce the data and
then _nish o_ the computations in R.
Work on a small subset of the data _rst to get the code working correctly. You can check the results
by doing the equivalent computations in R. Then run it on the larger data set. Make certain to try
this regardless of how powerful and capable your computer is. If your computer is not capable of
running on the full data set, run it for di_erent size input and show a plot of the time taken as a
function of number of lines processed.
Shell commands that may be useful include: sed, egrep,wc, sort, uniq, cut, man, ls, gunzip, tr,
head, tail, echo, cat, xargs. You probably don't need them all.
2 Basebal, Databases and SQL
In this part of the assignment, you will gain experience with databases and SQL, and of course R,
data manipulation and visualization.
2.1 Data
We will use data about many, many aspects of baseball. This data has been compiled by Sean
Leahman and he has kindly made them available for use by many. Je_ Knecht has made the
data, up to 2011, available as an SQLite database. It is available via cloning a git repository
(https://github.com/jknecht/lahmann-2013.sqlite) You can also retrieve from the class Web
site at http://eeyore.ucdavis.edu/stat141/Data/lahman2013.sqlite. As we saw in class,
there are 24 tables in this database. Each table has columns and rows. Documentation for each of
the tables is available at http://seanlahman.com/files/database/readme2013.txt.
2.2 Software
2. You will need to install the RSQLite package,typically using install.packages().
2.3 Questions
You can answer these questions with a combination of SQL commands and R manipulation of the
results, if necessary.
Give the answer and show the SQL and R code used to answer each question.
1. What years does the data cover? are there data for each of these years?
2. How many (unique) people are included in the database? How many are players, managers, etc?
3. What team won the World Series in 2000?
4. What team lost the World Series each year?
5. Do you see a relationship between the number of games won in a season and winning the World
Series?
6. In 2003, what were the three highest salaries? (We refer here to unique salaries, i.e., more than
one player might be paid one of these salaries.)
7. For 1999, compute the total payroll of each of the di_erent teams. Next compute the team
payrolls for all years in the database for which we have salary information. Display these in a plot.
8. Study the change in salary over time. Have salaries kept up with ination, fallen behind, or
grown faster?
9. Compare payrolls for the teams that are in the same leagues, and then in the same divisions.
Are there any interesting characteristics? Have certain teams always had top payrolls over the
years? Is there a connection between payroll and performance?
10. Has the distribution of home runs for players increased over the years?
When answering the questions, try to summarize the results in convenient and informative form
(e.g. tables and/or plots) that illustrate the key features.
2.4 Bonus Questions
Students who are looking for bonus points (e.g., to makeup for other assignments) can compose
additional questions and answer these. Make certain to explicitly state each question, indicate why
it is interesting, and answer it using the data,providing conclusions, evidence and the code used
to answer the question.