Tag: Mathematics

Please see attached word doc lab for instructions. The whole lab please. Brief explanations would be great so that I can study.

Thank you so much

Refer to Sheets 1, 2, and 3 from the Marseille residential building plans in the Large Prints supplement to answer the
following questions. fill in your answers in the 12-2 activity complete the 10 questions and save as a pdf . Attached 12’2′ activity, powerpoint, and the Marseille residential building plans

All work must be show on the attached Excel document (:

Each question should be clearly labeled and put on a separate sheet in the excel doc.

The final product should be the attached excel doc with a sheet for each question (For a total of 4 sheets).

#2

Propose how you will conduct your own six-question survey.

Introduction

Note: Do not complete this assessment until you have received faculty feedback on Assessment 1.

The survey you are designing will include describing the population of interest and the sampling method you intend to use. In the next assessment, you will use a data survey generator to produce responses to those questions.

Demonstration of Proficiency

By successfully completing this assessment, you will demonstrate your proficiency in the following course competencies through the following assessment scoring guide criteria.

• Competency 1: Interpret a data set’s central tendency and variability using descriptive statistical procedures.
  • Estimate potential response values for survey questions.
• Competency 2: Evaluate the adequacy of data collection methods.
  • Explain why a specified sampling strategy for a survey is appropriate.
  • Develop survey questions for a study.

Note: Do not complete this assessment until you have received faculty feedback on Assessment 1.

Use the Data Collection Template [DOC] to complete the assessment. Make sure you address each of the three questions in detail and fill in all the required information in the table.

This assessment is the second step in the process of developing a survey. In this assessment, you will define your data collection strategy, which includes developing six survey questions. To allow you to focus your time and effort on the actual survey tool and analysis, this course uses a software program to provide the data. Using technology to generate survey data causes hypothetical restrictions in your survey design. As a result, the number and type of questions you write for your survey must follow the Data Collection Template for this assessment.

Note: After you submit your survey questions, faculty will provide feedback on them. When you receive feedback, you can proceed with data collection using the Survey Data Generator in Assessment 3.

Directions

Develop six questions for your survey. Keep in mind that you will not be conducting the survey by mailing or e-mailing questionnaires. Your survey responses will be determined by an electronic survey generator, which accepts only certain types of questions; therefore, the types of questions you can ask for this assessment are very specific and must adhere to the guidelines listed below. In the future, as you design surveys to solve problems or answer key questions in your professional life, you will likely draw from a broader range of question types.

Guidelines for the Questions

• All six survey questions should be stated in question form. They should be written like they are being asked directly to a survey participant. For example, you would ask “How many cats do you own?” rather than stating “The number of cats owned.”
• The first four questions (1–4) must be binary—that is, they have only two possible responses. Examples of this are yes/no, true/false, and male/female (to name a few).
• The last two questions (5 and 6) must be quantitative. These questions have to elicit a single numeric response. Survey participants can respond with only one number.
• There are certain types of questions that are not within the parameters of the project. The following types of questions cannot be asked:
  • Do not ask questions where survey participants have to explain something. This includes short answer and fill-in-the-blank questions.
  • Do not use a Likert scale, in which a participant would choose from responses such as strongly agree, agree, neutral, disagree, and strongly disagree.
  • Avoid questions where a participant chooses a number on a scale, such as 1 to 10 or 1 to 5.
  • Do not ask any questions that are contingent on another question. Each question must have a stand-alone response.
  • Do not ask questions that have already been answered by how you have defined your population. For example, if your population includes only males, do not ask “Are you male or female?”

Guidelines for the Minimum and the Maximum of the Questions

The minimum is the lowest number that you think a participant can or will respond with. The maximum value is the largest value that you think a participant can or will respond with. To determine these values, make an educated estimate based on your population and the research you have conducted on the issue. For example, if we are surveying Capella learners, we might ask “What is your age?” In this situation, a minimum age might be 16, and a maximum age might be 85. Note that it is possible to be outside these ranges. The minimum and the maximum are approximations, or likely ranges, of what you expect.

• Your binary questions will not have a minimum or a maximum.
• You will need to set a minimum and a maximum for each of the quantitative questions.
• The minimum and the maximum are each one single number.

Guidelines for the Expected Values for Typical Responses to the Questions

The typical responses will help the program that generates your hypothetical data produce more realistic participant responses based on your knowledge of the issue you are studying. The typical response will fall between the minimum and the maximum. It is the value you think will be the most common response from a survey participant. Base the typical response on your knowledge of what you are surveying and the research you have conducted on the issue.

• You will not need to fill in a typical response for questions 1 through 4.
• The typical responses for the quantitative questions should be what you think the mean (average) of all the responses will be.
• The typical response is one single number.

Defining Your Data Collection Strategy

• Reminder: Use the Data Collection Template [DOC] to define your strategy.
• Include the following items in your strategy:
  • Your target population for the survey.
  • Your sampling strategy and how you would attempt to conduct your survey. Be sure to include some rationale for your strategy and any potential issues that might affect your survey results.
  • Your six survey questions following the guidelines presented above. Be sure to document the expected value along with a reasonable minimum value and maximum value in the table, as you will use these pre-survey values in later project components.
• In Table 1 of the Data Collection Template, fill in every box that says “you fill in” and then remove that message once you have done this. Your final product should have a response in every box; there should be no empty boxes in the table.

1. a. Show that this model has an unbounded solution by Big M Method. (25P)

b. What can be changed to have a bounded solution for this model? Explain by solving it. (25P)

Max Z= 3×1 + 6×2

s.to

3×1 + 4×2 ≥ 12

-2×1+ x2 ≤ 4

x1, x2 ≥ 0

Prioritise Kerouacaurus writer bidding at 75 USD

E–x-a-m Time: 26th Aug, 12am (Sydney Time) 24 hrs window

Duration : 1hr

Question structure:

The examination will consist of short answer conceptual questions and practical exercises/problem questions. The questions will be comparable to those covered in class; therefore, the best form of revision will be to work through lecture and tutorial questions, exercises and problems.

Topic covered: Similar to that screenshot attached

a) Find the value(s) of coefficient b such that the two polynomials f (x) = x + 1 and
g(x) = 1 + bx + x^2 are orthogonal to each other with respect to the L2-scalar
product

b) Find all Legendre coefficients for f: [−1,1]→R: x→x^3+1.

c) Find the 17th Legendre coefficient of the function f : [−1, 1] → R : x → sin(x^2).

d) Show by using Rodrigues’ formula that P1 and P2 are
orthogonal with respect to the scalar product defined in part (a).

1. For this lab, click on the link for the pdf file below to download the lab.

2. Complete the lab either by typing the work and answers or print the labs and write on the paper copies. If you aren’t able to print, then write the answers on blank paper. Show your work in the space provided! Please BOX and/or HIGHLIGHT your final answer. For assistance in the math when completing the lab on your computer, click on the following links to go to the indicated pages: How to Use the Math Equation Editor and How to Insert or Paste a Desmos Graph.

3. Once you have completed the problems, then submit your typed lab as a file to Canvas or scan your written copy and submit the pdf file to Canvas. Please do not upload a picture! Upload your scanned document on Canvas by clicking on “Submit Assignment.”

If you do not have access to a scanner, consider downloading the free version of a scanner app on your mobile device. These aps allow you to take a picture of a document and save it as a pdf file. Take pictures of all of the lab pages and save them as a single pdf document which you can then email to yourself and upload to Canvas. For further information, click the link to go to the page: How to Scan and Upload Submissions (in the Additional Resources for Students Module).

The main goal of the final project is to apply the concepts that you have learned throughout the course to real-world data. In this project first you need to explore the data through descriptive statistics and graphical summaries and then use multiple regression analysis to analyze the relationships between variables. The data set provided to you includes information on homes on the market by North Valley Real Estate.

The initial report for the project should be a 2-4 page paper (this does not include computer output/tables/graphs) that describes the details of each variable (types of the variable, summary statistics: mean, median, standard deviation, etc.) and shows the variable’s distribution using histograms or frequency polygons (or other graphical summary methods discussed in week 1).

The final report for the project should be a 6-10 page paper (this does not include computer output/tables/graphs) that describes the question of interest, how you used the data set to analyze the question with details on the steps you used in your analysis, your findings about the question of interest and the limitations of your study. Specifically, your report should contain the following:

1. Abstract: includes a one paragraph summary of what you set out to learn, and what you ended up finding. It should summarize the entire report.

• Introduction: includes a brief introduction about the data, a discussion of the question of interest: What properties of a home are related to its selling price on the market?

A brief overview of your methodology used to examine the research question, a summary of the results of your study, and an outline of the remaining organization of the paper.

3. Data Set: includes details about the variables in the data set, summary statistics, and visual tools to show the data (e.g. box plots, histograms, scatter graphs)

Note: You can include your initial report for this section.

4. Methodology and Results: includes testing if data meets the assumptions of regression (such as not correlated independent variables, linearity, and etc.), running the multiple regressions, using stepwise regression methodology to find the best model, providing inferences about the question of interest, and writing a detailed interpretation of the regression results (such as interpretation of the coefficients, ANOVA table, t tests, p-values, coefficient of determination, etc.) and discussion.

5. Limitations of study and conclusion: includes describing any limitations of your study and how they might be overcome in future research and provide brief conclusions about the results of your study.