STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup Page 1 of 4 Assignment #3: Inferential Statistics Analysis and Writeup Identifying Information Student (Full Name): Kayla Johnson...

1 answer below »
Attached are the first two parts of the assignment which are done but are needed to complete part 3. At the bottom of assignments 1&2 there is feedback I received from my professor. Assignment 3 template and data set is also attached.


STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup Page 1 of 4 Assignment #3: Inferential Statistics Analysis and Writeup Identifying Information Student (Full Name): Kayla Johnson Class: Instructor: Date: Part A: Inferential Statistics Data Analysis Plan and Computation Introduction: Variables Selected: Table 1: Variables Selected for Analysis Variable Name in the Data Set Variable Type Description Qualitative or Quantitative Variable 1: Socioeconomic Variable 2: Expenditure Variable 3: Expenditure Data Analysis: 1. Confidence Interval Analysis: For one expenditure variable, select and run the appropriate method for estimating a parameter, based on a statistic (i.e., confidence interval method) and complete the following table (Note: Format follows Kozak outline): Table 2: Confidence Interval Information and Results Name of Variable: State the Random Variable and Parameter in Words: Confidence interval method including confidence level and rationale for using it: State and check the assumptions for confidence interval: Method Used to Analyze Data: Find the sample statistic and the confidence interval: Statistical Interpretation: 2. Hypothesis Testing: Using the second expenditure variable (with socioeconomic variable as the grouping variable for making two groups), select and run the appropriate method for making decisions about two parameters relative to observed statistics (i.e., two sample hypothesis testing method) and complete the following table (Note: Format follows Kozak outline): Table 3: Two Sample Hypothesis Test Analysis Research Question: Two Sample Hypothesis Test that Will Be Used and Rationale for Using It: State the Random Variable and Parameters in Words: State Null and Alternative Hypotheses and Level of Significance: Method Used to Analyze Data: Find the sample statistic, test statistic, and p-value: Conclusion Regarding Whether or Not to Reject the Null Hypothesis: Part B: Results Write Up Confidence Interval Analysis: Two Sample Hypothesis Test Analysis: Discussion: STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup - Instructions Page 1 of 5 STAT200 Introduction to Statistics Assignment #3: Inferential Statistics Analysis and Writeup Purpose: The purpose of this assignment is to develop and carry out an inferential statistics analysis plan and write up the findings. There are two main parts to this assignment: ● Part A: Inferential Statistics Data Plan and Analysis ● Part B: Write up of Results Part A: Prepare Data Plan, Analyze Data, and Complete Part A of the Assignment #3 Template ➢ Task 1: Select Variables. Review the variables you used for assignments #1 and #2. Select your qualitative socioeconomic variable as your grouping variable and the two expenditure variables from the variables used in these previous assignments. Fill in Table 1: Variables Selected for Analysis with name, description, and type of variable (i.e., qualitative or quantitative). ➢ Task 2: Select and Run a One Sample Confidence Interval Analysis. For one expenditure variable, select and run the appropriate method for estimating a parameter, based on a statistic (i.e., confidence interval method). Complete Table 2: Confidence Interval Information and Results, which follows the format outlined by Kozak and the course’s problem-solving approach, including: ○ Random variable stated in words ○ Confidence interval method, including rationale and assumptions ○ Method used for analyzing data (i.e., web applets, Excel, TI calculator, etc.). ○ Results obtained ○ Interpretation ➢ Task 3: Select Two Sample Hypothesis Test. Using the second expenditure variable (with the socioeconomic variable as the grouping variable), select and run the appropriate method for making decisions about two parameters relative to observed statistics (i.e., two sample STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup - Instructions Page 2 of 5 hypothesis test method). Complete Table 3: Two Sample Hypothesis Test Analysis, which follows the format outlined by Kozak and the course’s problem-solving approach, including: ○ Hypotheses (null and alternative). ○ Two sample hypothesis testing method, including rationale and assumptions ○ Method used for analyzing data (i.e., web applets, Excel, TI calculator, etc.). ○ Results obtained. ○ Interpretation (i.e., Reject the null hypothesis OR Fail to reject null hypothesis) Step 2: Write Up Results and Complete Part B of the Assignment #3 Template For this 1 to 2 page section, refer to the inferential statistics data plan and computations done for Part A of this assignment. Address the following area: ➢ Introduction. Based on the scenario you submitted for the second assignment, provide a brief description of scenario, including the variables that were used in this analysis. Include a completed “Table 1: Variables Selected for Analysis to show the variables you selected for analysis. ➢ Data Set Description and Method Used for Analysis. Briefly describe the data set, using information provided with data set and write up in Assignment #2. Also describe what method(s) (i.e., free web applets, Excel, TI Calculator) you used to analyze the data. ➢ Results. In this section, you will report the results of your inferential statistics data analysis. For the Confidence Interval Analysis, write one paragraph that includes: o Statistical method used, including rationale and whether assumptions were met. o Statistical Interpretation. The statistical interpretation is that the confidence interval has a probability (1−α, where α is the complement of the confidence level) of containing the population parameter. o Real World Interpretation. Explain the results in everyday language. Recommend reviewing the text and information from the classroom for examples on how to report results in everyday language. STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup - Instructions Page 3 of 5 For the Two Sample Hypothesis Test Analysis, write one paragraph that includes: o Hypotheses that were assessed. See below table for example format: Examples Format for Writing Null and Alternative Hypotheses, in Words Null Hypothesis: There is no significant difference in [insert variable name] between [insert group 1 name] and [insert group 2 name] households. Alternative Hypothesis: ➢ For two-tailed (≠): There is a significant difference in [insert variable name] between [insert group 1 name] and [insert group 2 name] households. ➢ For one-tailed (>): [Insert group 1 name] has statistically significantly higher [insert variable name] than [insert group 2 name]. ➢ For one-tailed (<): [insert="" group="" 1="" name]="" has="" statistically="" significantly="" lower="" [insert="" variable="" name]="" than="" [insert="" group="" 2="" name].="" o="" statistical="" method="" used,="" including="" rationale="" and="" whether="" assumptions="" were="" met.="" see="" below="" table="" for="" example="" format:="" example="" format="" for="" writing="" statistical="" method="" with="" rationale="" to="" determine="" whether="" the="" there="" was="" a="" difference="" in="" [insert="" household="" expenditure]="" between="" [insert="" names="" of="" two="" groups),="" a="" [insert="" name="" of="" hypothesis="" test="" used]="" was="" used.="" it="" was="" the="" appropriate="" statistical="" method,="" because="" [insert="" rationale].="" the="" assumptions="" were="" assessed="" [insert="" information="" about="" the="" assumptions="" assessed="" and="" whether="" they="" were="" met].="" o="" conclusion="" from="" the="" results.="" this="" is="" where="" you="" state="" whether="" to="" reject="" ho="" or="" fail="" to="" reject="" ho="" including="" the="" p-value="" that="" was="" obtained.="" the="" rule="" is:="" if="" the="" p-value="">< α, then reject ho. if the p-value ≥α, then fail to reject ho. stat200: assignment #3 - inferential statistics analysis and writeup - instructions page 4 of 5 o real world interpretation. explain, in everyday language, the results. if any of the assumptions were not met, describe how it might affect conclusions. address issues of type i and/or type ii error, where appropriate. recommend reviewing the text and information from the classroom for examples on how to report results in everyday language. ➢ discussion– write one paragraph that summarizes the results of your findings and how they may be helpful to the person described in the scenario, when making a household budget. assignment submission: name the file that contains your completed assignment #3 inferential statistics analysis - template using the following format: “assignment3-studentlastname.” submit it via the assignments area in the leo classroom in the “assignment #3: inferential statistics analysis and writeup” folder. grading rubric for assignment #3 part a: prepare data plan, analyze data, and complete part a of the template selection of variables and completion of table 10% selection and calculation of confidence interval analysis: ● selection of appropriate test and rationale ● assumptions ● method used and calculation ● conclusion ● statistical interpretation 20% selection and calculation of two sample hypothesis test: ● research question and hypotheses ● selection of appropriate test and rationale ● assumptions ● method used and calculation ● conclusion, including p-value ● statistical interpretation 20% part b: write up of results introduction and description of data set 5% stat200: assignment #3 - inferential statistics analysis and writeup - instructions page 5 of 5 confidence interval. summarized: ● statistical method used, including rationale and whether assumptions were met ● statistical interpretation ● real world interpretation. 15% two sample hypothesis test. summarized: ● hypotheses ● statistical method used, including rationale and whether assumptions were met. ● conclusion from the results. ● real world interpretation. 15% discussion 5% wrote clearly, concisely, and with few errors. easy to understand. 10% stat200 introduction to statistics assignment #1: descriptive statistics data analysis plan name: kayla johnson class: stat200 date: january 26, 2020 scenario: to decide the household budget one should look for, what is the total household income and what will be the total expenditure including spend on food, housing and transportation according to his/her socio-economic conditions such as marital status, age and family size. further, he/she can get the total household expenditure by adding the all the expenses and compare it with the total household income. if the total expenditure exceeds the total income, then they should manage their expenses accordingly so that they can survive. example: a 35 year old single parent with a high school diploma and one child should look for his/her income, and family size as socio-economic variables and then look for distribution of expenses on ‘annual expenditure’, ‘food’ and ‘housing’ and compare it with his/her total income. variables selected for the analysis: for the analysis you should select ‘income’ as one socio-economic variable and for two additional socio-economic variables we can select ‘marital status’ and ‘family size’. two expenditures for our analysis should be ‘annual expenditure’ and expenses on ‘food’. descriptions of variables selected for analysis: variable name variable type variable description coding se-marital status qualitative marital status of head of household not married/married se-income quantitative annual household income amount in us dollars se-family size quantitative total number of people in α,="" then="" reject="" ho.="" if="" the="" p-value="" ≥α,="" then="" fail="" to="" reject="" ho.="" stat200:="" assignment="" #3="" -="" inferential="" statistics="" analysis="" and="" writeup="" -="" instructions="" page="" 4="" of="" 5="" o="" real="" world="" interpretation.="" explain,="" in="" everyday="" language,="" the="" results.="" if="" any="" of="" the="" assumptions="" were="" not="" met,="" describe="" how="" it="" might="" affect="" conclusions.="" address="" issues="" of="" type="" i="" and/or="" type="" ii="" error,="" where="" appropriate.="" recommend="" reviewing="" the="" text="" and="" information="" from="" the="" classroom="" for="" examples="" on="" how="" to="" report="" results="" in="" everyday="" language.="" ➢="" discussion–="" write="" one="" paragraph="" that="" summarizes="" the="" results="" of="" your="" findings="" and="" how="" they="" may="" be="" helpful="" to="" the="" person="" described="" in="" the="" scenario,="" when="" making="" a="" household="" budget.="" assignment="" submission:="" name="" the="" file="" that="" contains="" your="" completed="" assignment="" #3="" inferential="" statistics="" analysis="" -="" template="" using="" the="" following="" format:="" “assignment3-studentlastname.”="" submit="" it="" via="" the="" assignments="" area="" in="" the="" leo="" classroom="" in="" the="" “assignment="" #3:="" inferential="" statistics="" analysis="" and="" writeup”="" folder.="" grading="" rubric="" for="" assignment="" #3="" part="" a:="" prepare="" data="" plan,="" analyze="" data,="" and="" complete="" part="" a="" of="" the="" template="" selection="" of="" variables="" and="" completion="" of="" table="" 10%="" selection="" and="" calculation="" of="" confidence="" interval="" analysis:="" ●="" selection="" of="" appropriate="" test="" and="" rationale="" ●="" assumptions="" ●="" method="" used="" and="" calculation="" ●="" conclusion="" ●="" statistical="" interpretation="" 20%="" selection="" and="" calculation="" of="" two="" sample="" hypothesis="" test:="" ●="" research="" question="" and="" hypotheses="" ●="" selection="" of="" appropriate="" test="" and="" rationale="" ●="" assumptions="" ●="" method="" used="" and="" calculation="" ●="" conclusion,="" including="" p-value="" ●="" statistical="" interpretation="" 20%="" part="" b:="" write="" up="" of="" results="" introduction="" and="" description="" of="" data="" set="" 5%="" stat200:="" assignment="" #3="" -="" inferential="" statistics="" analysis="" and="" writeup="" -="" instructions="" page="" 5="" of="" 5="" confidence="" interval.="" summarized:="" ●="" statistical="" method="" used,="" including="" rationale="" and="" whether="" assumptions="" were="" met="" ●="" statistical="" interpretation="" ●="" real="" world="" interpretation.="" 15%="" two="" sample="" hypothesis="" test.="" summarized:="" ●="" hypotheses="" ●="" statistical="" method="" used,="" including="" rationale="" and="" whether="" assumptions="" were="" met.="" ●="" conclusion="" from="" the="" results.="" ●="" real="" world="" interpretation.="" 15%="" discussion="" 5%="" wrote="" clearly,="" concisely,="" and="" with="" few="" errors.="" easy="" to="" understand.="" 10%="" stat200="" introduction="" to="" statistics="" assignment="" #1:="" descriptive="" statistics="" data="" analysis="" plan="" name:="" kayla="" johnson="" class:="" stat200="" date:="" january="" 26,="" 2020="" scenario:="" to="" decide="" the="" household="" budget="" one="" should="" look="" for,="" what="" is="" the="" total="" household="" income="" and="" what="" will="" be="" the="" total="" expenditure="" including="" spend="" on="" food,="" housing="" and="" transportation="" according="" to="" his/her="" socio-economic="" conditions="" such="" as="" marital="" status,="" age="" and="" family="" size.="" further,="" he/she="" can="" get="" the="" total="" household="" expenditure="" by="" adding="" the="" all="" the="" expenses="" and="" compare="" it="" with="" the="" total="" household="" income.="" if="" the="" total="" expenditure="" exceeds="" the="" total="" income,="" then="" they="" should="" manage="" their="" expenses="" accordingly="" so="" that="" they="" can="" survive.="" example:="" a="" 35="" year="" old="" single="" parent="" with="" a="" high="" school="" diploma="" and="" one="" child="" should="" look="" for="" his/her="" income,="" and="" family="" size="" as="" socio-economic="" variables="" and="" then="" look="" for="" distribution="" of="" expenses="" on="" ‘annual="" expenditure’,="" ‘food’="" and="" ‘housing’="" and="" compare="" it="" with="" his/her="" total="" income.="" variables="" selected="" for="" the="" analysis:="" for="" the="" analysis="" you="" should="" select="" ‘income’="" as="" one="" socio-economic="" variable="" and="" for="" two="" additional="" socio-economic="" variables="" we="" can="" select="" ‘marital="" status’="" and="" ‘family="" size’.="" two="" expenditures="" for="" our="" analysis="" should="" be="" ‘annual="" expenditure’="" and="" expenses="" on="" ‘food’.="" descriptions="" of="" variables="" selected="" for="" analysis:="" variable="" name="" variable="" type="" variable="" description="" coding="" se-marital="" status="" qualitative="" marital="" status="" of="" head="" of="" household="" not="" married/married="" se-income="" quantitative="" annual="" household="" income="" amount="" in="" us="" dollars="" se-family="" size="" quantitative="" total="" number="" of="" people="">
Answered Same DayFeb 26, 2021

Answer To: STAT200: Assignment #3 - Inferential Statistics Analysis and Writeup Page 1 of 4 Assignment #3:...

Monali answered on Mar 01 2021
137 Votes
10.1.6
                                    Value    Rental        Rental income
                                    81000    6656        Mean    9611
                                    95000    7904        Mode    8320
                                    121000    12064        Median    9568
                                    135000    8320        Standard deviation    2213
                                    145000    8320
                                    165000    13312
                                    178000    11856
                                    200000    12272
                                    214000    8528
                                    240000    10192
                                    289000    11648
                                    325000    12480
                                    77000    4576
                                    94000    8736
                                    115000    7904
                                    130000    9776
                                    140000    9568
                                    165000    8528
                                    174000    10400
                                    200000    10608
                                    208000    10400
                                    240000    12064
                                    270000    12896
                                    310000    12480
                                
    75000    7280
                                    90000    6240
                                    110000    7072
                                    126000    6240
                                    140000    9152
                                    155000    7488
                                    170000    9568
                                    194000    11232
                                    200000    10400
                                    240000    11648
                                    262000    10192
                                    303000    12272
                                    67500    6864
                                    85000    7072
                                    104000    7904
                                    125000    7904
                                    135000    7488
                                    148000    8320
                                    170000    12688
                                    190000    8320
                                    200000    8320
                                    225000    12480
                                    244500    11232
                                    300000    12480
Table #10.1.6 contains the value of the house and the amount of rental income in a year that the house brings in ("Capital and rental," 2013). Create a scatter plot and find a regression equation between house value and rental income. Then use the regression equation to find the rental income a house worth $230,000 and for a house worth $400,000. Which rental income that you calculated do you think is closer to the true rental income? Why?
- Regression Equation
y = 0.0244x + 5363.9
- Value of house = X = 230000
Rental = 0.0244 * 230000 +5363.9. Therefore, rental = 10,975.9
- Value of house = X = 40000
Rental = 0.0244 * 400000 +5363.9. Therefore, rental = 15,123.9
-Mean rental income is 9611 and median rental income is 9568. Based on these two statistic rental income of 10,975.9 ~~ 10,956 is close to actual rental income.
Rental - Value of house
Rental    y = 0.0244x + 5363.9
R² = 0.5848
81000    95000    121000    135000    145000    165000    178000    200000    214000    240000    289000    325000    77000    94000    115000    130000    140000    165000    174000    200000    208000    240000    270000    310000    75000    90000    110000    126000    140000    155000    170000    194000    200000    240000    262000    303000    67500    85000    104000    125000    135000    148000    170000    190000    200000    225000    244500    300000    6656    7904    12064    8320    8320    13312    11856    12272    8528    10192    11648    12480    4576    8736    7904    9776    9568    8528    10400    10608    10400    12064    12896    12480    7280    6240    7072    6240    9152    7488    9568    11232    10400    11648    10192    12272    6864    7072    7904    7904    7488    8320    12688    8320    8320    12480    11232    12480    Value of house
Rental
10.1.4
                                                Health Expenditure (% of GDP)    Prenatal Care (%)
                                                9.6    47.9
                                                3.7    54.6
                                                5.2    93.7
                                                5.2    84.7
                                                10    100
                                                4.7    42.5
                                                4.8    96.4
                                                6    77.1
                                                5.4    58.3
                                                4.8    95.4
                                                4.1    78
                                                6    93.3
                                                9.5    93.3
                                                6.8    93.7        Parental care %
                                                6.1    89.8        Mean    79.9
                                                            Median     89.8
                                                            Mode    93.7
                                                            Standard Deviation     19.5
The World Bank collected data on the percentage of GDP that a country spends on health expenditures ("Health expenditure," 2013) and also the percentage of women receiving prenatal care ("Pregnant woman receiving," 2013). The data for the countries where this information are available for the year 2011 is in table #10.1.8. Create a scatter plot of the data and find a regression equation between percentage spent on health expenditure and the percentage of women receiving prenatal care. Then use the regression equation to find the percent of women receiving prenatal care for a country that spends 5.0% of GDP on health expenditure and for a country that spends 12.0% of GDP. Which prenatal care percentage that you calculated do you think is closer to the true percentage? Why?
- Regression equation;
y = 1.6606x + 69.739
- GDP expenditure %, X = 5%
Parental care = y = 1.6606 *5 + 69.739 = 78.042
- GDP expenditure % X = 12%
Parental care = y = 1.6606 *12 + 69.739 = 89.6662
- Mean parental care % is 79.9 and Media is 89.8. Based on these two parameters parental care of 89.6662 ~~ 89.7 is closer to true value.
Prenatal Care (%)    y = 1.6606x + 69.739
R² = 0.0294
9.6    3.7    5.2    5.2    10    4.7    4.8    6    5.4    4.8    4.0999999999999996    6    9.5    6.8    6.1    47.9    54.6    93.7    84.7    100    42.5    96.4    77.099999999999994    58.3    95.4    78    93.3    93.3    93.7    89.8    
10.2.2
                                Table #10.1.6: Data of House Value versus Rental
                                    Value    Rental
                                    81000    6656
                                    95000    7904
                                    121000    12064
                                    135000    8320
                                    145000    8320
                                    165000    13312
                                    178000    11856
                                    200000    12272
                                    214000    8528
                                    240000    10192
                                    289000    11648
                                    325000    12480
                                    77000    4576
                                    94000    8736
                                    115000    7904
                                    130000    9776            Value    Rental
                                    140000    9568        Value    1
                                    165000    8528        Rental    0.7647157521    1
                                    174000    10400
                                    200000    10608
                                    208000    10400
                                    240000    12064
                                    270000    12896
                                    310000    12480
                                    75000    7280
                                    90000    6240
                                    110000    7072
                                    126000    6240
                                    140000    9152
                                    155000    7488
                                    170000    9568
                                    194000    11232
                                    200000    10400
                                    240000    11648
                                    262000    10192
                                    303000    12272
                                    67500    6864
                                    85000    7072
                                    104000    7904
                                    125000    7904
                                    135000    7488
                                    148000    8320
                                    170000    12688
                                    190000    8320
                                    200000    8320
                                    225000    12480
                                    244500    11232
                                    300000    12480
Table #10.1.6 contains the value of the house and the amount of rental income in a year that the house brings in ("Capital and rental," 2013). Find the correlation coefficient and coefficient of determination and then interpret both.
Correlation coefficient measures linear relationship between two variables, that is, how closely or spread out two variable data points are. Correlation coefficient is = √0.5048 = 0.7647. This means that variable of value explains rental to 76.47% which is very strong relationship exists between value and rental.
Coefficient of determination tells how well model explains and predict based on given regression. This is important statistic to look in conjunction to correlation coefficient to get complete...
SOLUTION.PDF

Answer To This Question Is Available To Download

Related Questions & Answers

More Questions »

Submit New Assignment

Copy and Paste Your Assignment Here