Answered You can buy a ready-made answer or pick a professional tutor to order an original one.
Unit IV Scholarly Activity Instructions Descriptive Statistics Analysis Describe the Sun Coast data using the descriptive statistics tools discussed in the unit lesson. Establish whether assumptions a
Unit IV Scholarly Activity
Instructions
Descriptive Statistics Analysis
Describe the Sun Coast data using the descriptive statistics tools discussed in the unit lesson. Establish whether assumptions are met to use parametric statistical procedures. Repeat the tasks below for each tab in the Sun Coast research study data set. Utilize the Unit IV Scholarly Activity template here.
You will utilize Microsoft Excel ToolPak. The links to the ToolPak are here in the Course Project Guidance document.
Here are some of the items you will cover.
§ Produce a frequency distribution table and histogram.
§ Generate descriptive statistics table, including measures of central tendency (mean, median, and mode), kurtosis, and skewness.
§ Describe the dependent variable measurement scale as nominal, ordinal, interval, or ratio.
§ Analyze, evaluate, and discuss the above descriptive statistics in relation to assumptions required for parametric testing. Confirm whether the assumptions are met or are not met.
The title and reference pages do not count toward the page requirement for this assignment. This assignment should be no less than five pages in length, follow APA-style formatting and guidelines, and use references and citations as necessary
- @
- 1030 orders completed
- ANSWER
-
Tutor has posted answer for $30.00. See answer's preview
*********** ************** ** ******************* ** Affiliation:Data ******************* Data *** ************ ******************** ************ TablePM ************************************* DaysFrequency0-214-7618-93010-1211HistogramDescriptive ********** **************** dayMean565728155Mean7126214Standard Error025560014Standard Error0186484Median6Median7Mode8Mode7Standard Deviation259405814Standard ********************** *********************** Variance3581953Kurtosis-08521619Kurtosis0124923Skewness-037325713Skewness014225Range98Range10Minimum02Minimum2Maximum10Maximum12Sum5827Sum734Count103Count103Largest(1)10Largest(1)12Smallest(1)02Smallest(1)2Confidence Level ************************* Level ****************************** TestThe ********** **** ******* *** ****** **** ******** has no *********** difference ** *** **** **** relates ** ****** ************* ***** ** * *********** ********** that ******* ******* the ****** **** ** **** ** normal ************* ** ***** ** ** *** ******* the test ********* *** p ***** ************************* ** reject *** **** ********** ******* null hypothesis ** ******************* ScaleOrdinalMeasure ** ******* ************************* ***** *********** ********** *** indifferences ** the test ****** of *** ****** **** ** that ** normal ********** **** ******************** for parametric testingThe assumptions in *** ********** ******* **** *** *** as there *** ************* in *** results ***** * ** ******* ********** interval ***** ***** *** *********** ** *** **** which *** to *********** ** the ******** ** ******* ******** *** ******** the **** ** the data for ******* *** **** day ** projected ** **** ** *** *** that ** 712 ************ ******* having similar counts **** was also * ********** **** ***** between *** ******* *** ****** ****** ** the **** ******** Additionally ********** ** *** **** ****** *** *** *** *********** **** *********** ******* **** *** assumptions ** *** ********** ******* ******** **************** Data *** Assumptions: ****** ******************* Distribution TableExpenditureFrequency20-500108501-1000761001-1500271501-2000112001-25001TimeFrequency0-50651-10026101-20098201-30085301-4008HistogramDescriptive ********** Tablesafety ******** *************** **** ************************************** Error314770075Standard Error4803089Median507772Median190Mode234Mode190Standard *************************** ********************** ************************ ********************************************************************************************************************************************************************************************************************************************************* ***** ************************** ***** ******************************* ********* null *** *********** ********** *** normality hereH0: The sample **** **** ******* to training *********** is ********* to **** ** **** time hoursH1: ***** ** * *********** ********** value between the data in ******** *********** and **** ** lost **** ******** ** ***** ** ** *** provide *** **** ********* *** * ***** hereP>005P≤005Accept ** ****** *** **** ********** ****** accept *** **** hypothesisMeasurement ******************* of ******* *************************** p ***** for both ******** expenditures *** the lost **** hours is *********** *************** for ********** ******* *** *********** *** parametric ******* in *** ***** prove ** ** met as ********* ** *** **** ********* ***** ***** ** a **** difference **** emerges ** *** **** ******* *** ******** expenditure *** *** **** time hours ******** from the *********** **** ********* **** *** * value ** **** *** ******** *********** and **** **** ***** is ********* **** ******* ** ******** ** *** **** indicates **** ***** **** time ***** has a ******* ********** ******** ** ******* to **** ** ******** *********** **** *** statistical tests ****** *** assumptions as ***** is * ***** ********** **** emerges ** *** two **** setsDescriptive **** and ************ ******** ******************* ************ ****************************************************************************** HistogramDescriptive ********** ******************************* Error0177945Median125721Mode127315Standard ********************** ********************************************************************************************************************* TestState null *** *********** hypotheses *** ********* ******* ***** is ** relationship ******* *** * and * ************ ****** *** **** an alpha ** ** *** ******* the **** ********* *** * level ******************* or ****** *** **** ********** ********************* ScaleInternalMeasure ** ******* TendencyMeanEvaluationThere is ** direct ******** ******* *** ******************** for ********** testing *** assumptions *** parametric ******* **** ***** as ** ** ******* that ** no ************ ******* *** ********* In **** ************* there ** a null ********** *** **** variable ** ********** **** the variables ** *** *** ** the ******** regression ******** Since the ******** do *** **** *** relations ***** ******* * standard error ** the data ***** the **** hypothesis *** ****** ***** ** less *********** ** ********* * **** ********* ***** on *** data ******** **** is because ***** are *** ********* ** *** expense ** ***** **** ***** *** ********** assumptions to ****** ***** as there ** no clear relationshipDescriptive **** *** Assumptions: *********** Samples t ************* ************ ******************************************************************************************************************************* ********** ********** TrainingRevised ************************************** ******************** Error0659479Median70Median85Mode80Mode85Standard Deviation1104556Standard ********************** ********************* Variance2696457Kurtosis-077668Kurtosis-035254Skewness-00868Skewness0144085Range41Range22Minimum50Minimum75Maximum91Maximum97Sum4327Sum5256Count62Count62Largest(1)91Largest(1)97Smallest(1)50Smallest(1)75Confidence ***** *********************** ***** ****************************** ********* **** and *********** ********** *** ********* hereH0=0H1>0Use ** ***** ** 05 and ******* *** **** ********* *** * ***** ******** 0Accept or reject *** **** hypothesis *************** ******** test data ** *** appendixMeasurement ScaleInternalMeasure of Central *************************** ** an ******** relationship between the sample data *** *** normal populationAssumptions *** parametric ********** *********** **** met ********** **** ******** **** *** *********** **** ** ***** than *** p ***** *** ******** ** the first **** *** * ***** ** ** whereas *** second **** *** a * value ** *** *** * value is greater **** **** ********* **** ***** ** * indirect relationship of the **** ** evidenced ** the * ***** *** dependent ********* **** normally distributed ************ ***** *** *** ****** ***** are *********** ** **** ***** **** ** *** **** ****** for *** revised ******** and that of ***** training ********* there ** ** ******** ************ ** *** data ******************* Data *** ************ ********* ******* t TestFrequency ************ ************************************************************************************************************************* ********** TablePre-Exposure μg/dLPost-Exposure μg/dLMean328571429Mean3328571Standard Error175230655Standard Error1781423Median35Median36Mode36Mode38Standard ************************** Deviation1246996Sample *********************** Variance1555Kurtosis-057603713Kurtosis-065421Skewness-042510965Skewness-048363Range50Range50Minimum6Minimum6Maximum56Maximum56Sum1610Sum1631Count49Count49Largest(1)56Largest(1)56Smallest(1)6Smallest(1)6Confidence ***** ************************* Level ******************************* ********* **** *** alternative hypotheses for ********* ******* **************** ** ***** ** ** *** ******* *** **** ********* *** p level hereα=005t=m1-m2/Sd/n3328571-328571429=04285671/17523t=024457Accept ** ****** *** **** ********** ********************* ScaleIntervalMeasure of Central ************************* null ********** ** ******** as *** null ********** is ******* **** ************ *** ********** ******* *** *********** for ********** testing **** met **** ** ******* *** **** ********* of ********* ******** which **** ********** on a ***** basis ************ the observations ** the data ********* **** *********** ** one ******* **** ** ************ ** *** **** **** ********* variables **** ******** *********** * ********** ** *** *** ***** ********* **** there is *********** ********** ******* the mean ** *** data ******* *** ********** ******* the **** ** 04285671 ** ********** ** *** *********** **** ********* **** *** t-test ** greater **** *** ********** **** *** differences ******* *** ******** * test *** *** ********** ****** leads ** ********** ** *** **** ********************* **** *** ************ ************** ************ ********************************************************************************************************************************************************* ********** ****** * AirB * ************************ Error0684028Standard ********************************************* ************************ ********************** ********************* ************************************************************************************************************************************************************************************************************ Level(950%)1431688Confidence ******************* = ****** * *************************** Error0575829Standard ******************************************** ************************ ********************** Variance6631579Sample Variance1410526Kurtosis-023752Kurtosis0253747Skewness0760206Skewness0159183Range9Range5Minimum3Minimum3Maximum12Maximum8Sum140Sum108Count20Count20Largest(1)12Largest(1)8Smallest(1)3Smallest(1)3Confidence ***** (950%)1205224Confidence ***** (950%)055584Kolmogorov-Smirnov TestState **** *** *********** ********** *** ********* ******* ***** ** ** ********** ** *** ******** ***** *** not *** ******** ** ***** ** 05 and ******* *** **** statistic *** p ***** **** α=005Test ********* ** water ** *********************** ********* ** *** ** soil(89-91)2=00004Accept ** ****** the **** ********** ********************* ***************** ** Central ************************* means *** not ***** ** **** **** on ********* **** of dataAssumptions *** ********** ******* ***** ** *** **** provided *** *********** that *** be ******* *** ***** *** ********* ***** ******** *** **** ** *********** ****** **** *** **** ***** ** an *********** ** *** ********* **** no ************ The ********** *********** ** **** ******** would relate ** *** parameters ** *** ********** distribution **** which **** ** drawn ************ a ************** **** would ***** to **** ***** ***** no such *********** **** ***** to normal distribution *********** ** *** ********* ******** ****** ***** ******* ** the **** variance ** well ** ********* ** the independent ************* **** *** *********** ****** *** **** ** ********
