RESPONSE

Introduction:

In the report, there are procedures involved in the establishment of performance evaluation. The evaluation takes into effect the performance appraisals guidelines in consideration of the managers in their respective regions.

One of the most usual applications of Statistics is describing a set of data using Pivot table. Pivot table is used to display cube query result. There can be multiple pivot tables placed in an Excel sheet which can be placed easily in the excel sheet. The slicer can also be used in multiple pivot tables easily. The pivot table can also be spanned across the multiple excel sheets easily

Given a set of data, for instance, the data on comparison among attributes of popularity of our undergraduate classes. By analyzing and examining the raw data, we can make and draw logical conclusions or even compare, contrast or rank the data or establishments based on the specified attribute. Evaluating the status of any sort of data by considering its attributes that effect on public is a very important aspect for the growth, examine and development of population

The use of Pivot table Analysis measures are the most effective ways to examine the data. To name some, one needs to employ the application of measures of central tendencies, measures of variability, and positions, estimation and correlation. Once data are gathered and analyzed, one will be aware of the attribute given the most importance by the population of the data, and also those given the least importance. Fortunately, Excel has a feature called pivot tables that can solve all these problems. Pivot tables quickly summarize long lists of data. By using a pivot table, you can calculate summary information without writing a single formula or copying a single cell. But the most notable feature of pivot tables is that you can arrange them dynamically. For example, say you create a pivot table summary using raw census data. With the drag of a mouse, you can easily rearrange the pivot table so that it summarizes the data based on gender or age groupings or geographic location. This process of rearranging your table is known as pivoting your data: you're turning the same information around to examine it from different angles

Objective: The goal of this assignment is to give more comfort investigating a data set that is unknown, and will require some data cleaning before you can make use of it. Preparing the data to be interpreted generally is the most labour-intensive part of analysis. This assignment will stretch your critical thinking skills, as you are given less direction by design. In a professional situation, will often be given even less direction, and be expected to use your resources to answer the questions that come up along your analytical process.

To analyze the 18-19 academic year (summer, fall, winter, spring) enrolment by course and term. The new Provost in an attempt to convince her to invest more money in the undergraduate business program because we are growing both online and on campus.

Discussion:

From the above table we can see that the most popular undergraduate class is BA, it has the total 7289 Prior Enrolment out 14755 during 2018 and 2019. The rate

Term	(All)
Row Labels	Count of Schedule_Type	Count of Meeting_Location_1	Count of Meeting_Time_1
ACTG	136	136	83
BA	366	361	230
FIN	74	74	48
GSCM	37	37	9
ISQA	20	20	6
MGMT	125	123	39
MIM	12	12	3
MKTG	83	83	59
MTAX	15	14	4
RE	24	24	13
Grand Total	892	884	494

The fall BA term is the most popular and which is the least and MIM is the least popular.

Term	(All)
Row Labels	Count of Schedule_Type
ACTG	136
BA	366
FIN	74
GSCM	37
ISQA	20
MGMT	125
MIM	12
MKTG	83
MTAX	15
RE	24
Grand Total	892

The above chart shows BA with greatest overall enrolment. The chart also shows that MIM has the least overall enrolment. Different other courses apart from RE are also not doing well. These courses include: ISQA, MTAX, FIN, and GSCM that has lower poll in terms of total enrolment the last two years.

I’ve learned in the past how to create the Pivot Table but never been able to utilize it in research. This is great way to evaluate data and compare them. I already started creating Pivot tables for the monthly actuals of income and expenses to determine the shorts and weaknesses in my property performance.

Total

ACTG BA FIN GSCM ISQA MGMT MIM MKTG MTAX RE 136 366 74 37 20 125 12 83 15 24

Term(All)

Campus(All)

Row LabelsCount of Schedule_TypeSum of Prior_Enrl

ACTG1361843

BA3667829

FIN741491

GSCM37281

ISQA2057

MGMT1251514

MIM1239

MKTG831386

MTAX15136

RE24179

Grand Total89214755

TermWinterTermFall

CampusICampusI

Row LabelsCount of Schedule_TypeSum of Prior_EnrlRow LabelsCount of Schedule_TypeSum of Prior_Enrl

ACTG420ACTG441005

BA920BA1083655

Grand Total1340FIN21572

GSCM19145

ISQA433

MGMT39618

MIM50

MKTG27602

MTAX552

RE571

Grand Total2776753

TermSpringTermSummer

CampusICampusI

Row LabelsCount of Schedule_TypeSum of Prior_EnrlRow LabelsCount of Schedule_TypeSum of Prior_Enrl

ACTG34703ACTG16135

BA933003BA481171

FIN29674FIN19245

GSCM15136GSCM20

ISQA718ISQA96

MGMT46715MGMT23181

MIM20MIM439

MKTG27562MKTG18222

MTAX441MTAX643

RE1683RE325

Grand Total2735935Grand Total1482067

TermWinterTermFall

CampusSCampusS

Row LabelsCount of Schedule_TypeSum of Prior_EnrlRow LabelsCount of Schedule_TypeSum of Prior_Enrl

BA10BA50

Grand Total10FIN10

Grand Total60

TermSpringTermSummer

CampusSCampusS

Row LabelsCount of Schedule_TypeSum of Prior_EnrlRow LabelsCount of Schedule_TypeSum of Prior_Enrl

Grand TotalGrand Total

TermWinterTermFall

CampusVCampusV

Row LabelsCount of Schedule_TypeSum of Prior_EnrlRow LabelsCount of Schedule_TypeSum of Prior_Enrl

BA10BA60

Grand Total10FIN40

MGMT30

MKTG50

Grand Total180

TermSpringTermSummer

CampusVCampusV

Row LabelsCount of Schedule_TypeSum of Prior_EnrlRow LabelsCount of Schedule_TypeSum of Prior_Enrl

Grand TotalBA120

GSCM10

MGMT140

MIM10

MKTG60

Grand Total340