Start Up Muster: Statistical Metrics and Data Management

Running head: START UP MUSTER
START UP MUSTER
Name of student:
Name of university:
Author’s note:

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START UP MUSTER
Table of Contents
Introduction....................................................................................................................2
Discussion......................................................................................................................2
Statistical metrics.......................................................................................................2
Data management and collection...............................................................................3
Summary of key points..............................................................................................4
Conclusion......................................................................................................................5
Bibliography...................................................................................................................7

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START UP MUSTER
Introduction
This report aims to discuss and evaluate the start-up muster report and provide
appropriate summary. An appropriate synopsis of the report is provided along with key-
insights, and some detailed comments on the methods that are used is provided in this report.
The presentation methods that are used in this report is provided in this report. The
appropriate statistical metrics from the report of start-up muster is provided in this report.
The start-ups plays a crucial role in the introduction of innovative services and
products in the markets, and finally creating opportunities for exporting, creating jobs and
then delivering economic prosperity for everyone.
Discussion
Statistical metrics
The Data61, the world leaders in the research of data science has been engaged for
creating an estimate on the statistics of the startups in the country, Australia on the five years
of the data of startup muster. It is essential that the Startup Muster manually reviews each of
the participant in the surveys and it only accepts the companies addressing a huge market in
any scalable methods that intends to eliminate the significant proportion of the self-identified
startups. After conducting the surveys, it is observed that the gender initiating the startups is
majorly the male gender as the statistics show. The aspect of good data needs to be both
actionable and accurate. The data from 178 distinct data points in the year, 2018 and it is
observed that majority of the data is the result of an organisation that wishes to gain
knowledge about any specific attribute for providing enhanced support to the startups. In the
year, 2015 954 new startups have been implemented and it is observed to be increased to
1085 in 2016 and the most number of startups that have been implemented in the last five
years is in the year 2017, with almost 1675 companies and then it decreased to 1465 in the