See File1st take home exam 1 MKT 870- ADVANCED MARKETING ANALYTICS TAKE HOME #1 ...

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See File1st take home exam   1  MKT	870-	ADVANCED	MARKETING	ANALYTICS		TAKE	HOME	#1	 Post	date:	October	13th,	Tuesday,	2020	 Due	date	for	submission:	Oct.18th,	Sunday,	2020	(via	Ping)	 Total	=	140	pts.		 	 This	is	our	first	take	home	exam.	By	its	very	nature,	the	exam	has	an	open	book	policy	where	you	can	use	 slides,	recordings,	HW	answers,	and	internet	to	search	for	more	information.	What	is	not	open	is	your	 peers	(i.e.,	working	together	on	the	exam	is	not	allowed).	Also	asking	me	a	question	on	whether	your	 answer	is	correct	or	whether	you	are	on	the	right	track	answering	the	question	is	also	not	allowed.	You	 can	raise	questions	if	you	are	in	need	for	more	clarity	on	the	questions.		 	 This	take-home	exam	questions	come	from	the	Workshop#1-Workshop#5.	You	have	access	to	the	 materials	to	be	able	to	answer	the	questions.		 	 For	Q1-	Q6	please	access	to	the	dataset	of	Subscription.csv	from	Basecamp.	For	Q7-Q9,	please	access	to	 the	dataset	of	amusement.csv	(Basecamp/Docs&	Files/Datasets).		 	 PART	1:	 	 Subscription.csv		dataset	is	about	a	firm	with	a	focus	on	subscription-based	service	and	is	collected	from	 N=300	respondents	based	on	several	demographical	and	behavioral	attributes.		 	 In	your	answers,	I	want	three	parts	to	be	submitted:	(1)	R	code,	(2)	R	output,	and	(3)	detailed	 interpretation	(if	I	am	asking	specifically	for	an	interpretation).		 	 Q1.	Please	examine	the	nature	of	the	dataset.	In	your	examination,	make	sure	that	you	list:	(i)	the	number	 of	rows	(respondents)	and	number	of	columns	(variables),		(ii)	the	data	types	of	each	variable,		(iii)	the	 first	3	and	the	last	3	rows	of	the	dataset,	(iv)	whether	there	is	any	missing	value	in	the	dataset,	(v)	some	 of	the	variables	are	character	types,	convert	them	into	factors	because	we	will	need	them	in	the	factor	 type	for	analysis,	and	(vi)	run	summary	statistics	of	the	dataset	(after	cleaning	the	missing	variables	if	 there	are	any).	Based	on	the	results	from	(i-vi),	talk	about	the	properties	of	the	dataset.	(15	pts)		 	 Q2.	Dataset	has	a	variable	called	“subscribe”	(whether	the	person	is	subscribed	to	a	service	or	not).	 Please	sort	the	data	based	on	subscription	behavior	(subNo	vs	subYes)	and	come	up	with	the	Summary	 statistics	for	each	subscription	behavior	separately.	Please	discuss	age,	gender,	income,	number	of	kids,	 whether	they	own	a	home	or	not,	and	what	customer	segment	they	belong	to.		Based	on	the	output	do	 you	see	any	difference	between	people	who	subscribe	to	the	service	and	who	don't?	(15	pts)	 	 Q3.	There	are	four	customer	segments	in	the	dataset.	Please	create	cross-tables	for	(i)	gender	and	 customer	segments,	(ii)	house	ownership	(Yes/No)	and	customer	segments,	(iii)	subscription	behavior	 (Yes/No)	and	customer	segment.	Make	sure	you	create	cross	tables	for	both	count	as	well	as	proportions.	 Please	discuss	your	findings.	(15	pts)	 	 Q4.	Let’s	examine	the	data	even	further	to	understand	the	segments.	Please	find	out	what	the	average	 income,	average	number	of	kids,	and	average	age	is	for	each	segment.	(15	pts)	 	 Q5.	Please	create	a	boxplot	for	income	vs.	customer	segments	in	the	same	output	(note:	income	is	on	the	 x-axis,	customer	segments	are	on	the	y-axis.	Please	interpret	the	findings	in	detail.	(10	pts).		 	 	  2  	 PART	2:		 	 Please	download	amusement.csv	to	solve	the	questions	below.	In	this	dataset,	respondents	report	their	 levels	of	satisfaction	with	different	aspects	of	their	experience	at	an	Amusement	park,	and	their	overall	 satisfaction	with	the	park.	You	will	also	see	how	distant	the	respondents’	locations	are,	whether	they	 visited	the	park	over	the	weekend	or	weekday,	and	their	number	of	kids	as	additional	variables.		 	 Q6.	Please	examine	the	nature	of	the	dataset.	In	your	examination,	make	sure	that	you	list:	(i)	the	number	 of	rows	(respondents)	and	number	of	columns	(variables),		(ii)	the	data	types	of	each	variable,		(iii)	the	 first	3	and	the	last	3	rows	of	the	dataset,	(iv)	whether	there	is	any	missing	value	in	the	dataset,	(v)	run	 summary	statistics	of	the	dataset	(after	cleaning	the	missing	variables	if	there	are	any).	Based	on	the	 results	from	(i-v),	talk	about	the	properties	of	the	dataset.	(15	pts)	 	 Q7.	Run	a	scatter	plot	matrix	for	all	the	variables	in	the	data	(note:	first	access	the	“car”	library	to	be	able	 to	run	the	scatterplot	matrix).	Check	the	distribution	of	each	variable.	List	the	ones	who	are	normally	 distributed	and	non-normally	distributed.	Transform	the	ones	that	are	not	normally	distributed	[note:	 you	can	use	any	transformation	method	you	want.	Make	sure	that	variable	is	normally	distributed	after	 the	transformation,	provide	evidence	that	they	are	normally	distributed	after	the	transformation](20	pts)	 	 Q8.	Run	the	correlation	matrix	between	all	the	variables	(except	‘weekend’–	that	is	a	categorical	 variable).	First,	download	corrplot	library	to	be	able	to	run	the	correlation	matrix.	Also,	find	the	 correlation	values	between	the	variables.	Interpret	the	findings.	(20	pts)	 	 Q9.	Run	the	scatter	plot	for	the	variables:	“overall”	satisfaction	and	“rides”	satisfaction.	Add	a	regression	 line	to	evaluate	the	strength	of	the	relationship	between	these	variables	(note:	you	are	not	running	a	 regression	analysis,	instead	just	adding	a	regression	line	to	evaluate	the	direction	and	strength	of	the	 relationship).	Please	discuss	the	findings.	(15	pts)	 	 	 	 BONUS	(10	pts).	Please	provide	your	opinion	on	the	course,	its	content,	and	execution.		 	 (i) Do	you	face	any	challenges	and	struggles	in	learning	R	and	if	yes,	which	aspect(s)	you	find	 most	challenging	in	your	learning	experience?		 (ii) So	far,	thinking	what	we	have	learned	in	the	class	with	R,	what	aspects	of	R	you	like?		 (iii) What	aspects	of	the	course	you	find	positive	about	your	learning	experience?	 (iv) What	aspects	of	the	course	can	be	improved	to	contribute	to	your	learning	experience?	 [basically,	what	else	can	be	done/or	differently	done	to	enhance	your	learning	process]

1st take home exam 1 MKT870-ADVANCEDMARKETINGANALYTICS TAKEHOME#1 Postdate:October13th,Tuesday,2020 Duedateforsubmission:Oct.18th,Sunday,2020(viaPing) Total=140pts....

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