Question

ANALYSIS An Australian manufacturing company is keen to develop new products and develop new product line of shoes so that the company can expand into Asian markets more than before. The data have been collected for 99 products from the market. The data are in an excel file named “SHOES”. The file includes: PRICE: Price of the shoes in dollars. GENDER: 1 for Female product and 2 for Male product. COUNTRY: the country in which the shoes is produced: 1 made in Thailand, 2 made in Singapore and 3 made in China. COST: Production cost of the shoes in dollars.

questions:

QUESTIONS Part 1: 1. Construct a pie chart for numbers of men and women shoes. Construct a pie chart for numbers for the three countries- Thailand, Singapore and China. Present your findings.

2. Construct a cross-classification table of frequencies between gender and country. Plot a vertical bar chart of frequency (Y variable) and gender (X variable), then group the bar charts of genders for three countries and comment on the relationship between gender and country

3. Determine if average prices for female shoes is less than average prices for male shoes. Compare the result with part 2 question

1. Does the result confirm your previous findings? (Follow the hypothesis testing steps, 0.05 level of significance, assuming “equal variances” of populations).

4. Using a scatter graph of price (Y variable on vertical axis) and production cost (X variable, horizontal axis), comment on the relationship between price and cost.

COST	GENDER	COUNTRY	PRICE
177	1	1	395
143	1	1	400
163	1	1	304
186	1	1	274
124	1	1	371
43	1	1	355
112	1	1	154
186	1	1	261
124	1	1	258
43	1	1	280
112	1	1	240
186	1	1	314
124	1	1	273
112	1	1	366
265	1	1	372
185	1	1	353
223	2	1	314
213	2	1	294
183	1	1	222
173	1	2	182
143	1	2	161
143	1	2	193
163	1	2	260
133	1	2	198
207	1	2	215
265	1	1	353
133	2	1	386
123	2	1	303
29	2	1	225
29	2	1	171
193	2	1	291
183	2	1	350
139	2	1	315
133	1	2	308
73	1	2	156
83	1	2	313
159	1	2	364
188	1	2	192
139	1	2	151
89	1	2	390
75	1	2	211
69	1	2	306
75	1	2	210
69	1	2	334
55	1	2	247
55	1	3	341
55	1	3	238
41	1	3	299
49	1	3	183
51	1	2	200
45	1	2	271
65	1	2	350
65	1	2	361
43	1	2	250
43	2	2	244
185	2	2	274
185	2	2	388
183	2	2	348
117	2	2	163
111	1	2	172
177	1	2	399
97	2	2	360
69	2	2	244
57	2	2	233
65	2	2	319
36	2	2	337
38	1	3	259
34	1	3	361
36	1	3	381
183	2	3	323
38	2	3	231
138	2	3	205
199	2	1	289
243	2	1	297
163	2	1	356
252	2	1	345
223	2	1	298
213	2	1	285
153	2	1	311
159	2	1	269
188	2	1	340
36	2	3	276
46	2	3	373
126	2	3	287
66	2	3	367
48	2	3	157
116	1	3	155
193	1	3	335
183	1	3	367
139	1	3	345
117	2	3	153
111	2	3	396
69	2	3	277
66	2	3	246
175	2	3	352
155	2	3	380
74	2	3	278
66	2	3	153
175	2	3	209

E

Answer 1

from the all results in R studio,

1.Female shoes are produced more than male shoes. For all country the shoes produced are approximately equal.

2. There is no relation between the Gender and country

3. From the results of t test ,p

value is greater than 0.05( level of significance). Therefore there is no significant difference in mean price of male and female.

4. From the scatter plot it seems that there is very weak positive correlation between price and cost of shoe.