FACULTY OF HEALTH AND APPLIED SCIENCES
DEPARTMENT OF MATHEMATICS & STATISTICS
Basic Business Statistics 1B
BBS112S
Information and Instructions:
• Assignment should be submitted in PDF file only.
• All students in any assignment group are expected to participate fully.
• All students in the same assignment group will earn the same marks.
• After submitting the assignment, the group may be asked to defend the
submission before the course lecturer (or his nominated representative). The
lecturer may nominate any member of a group to defend the submission on behalf
of the group.
• Each group should have a minimum of 4 students and a maximum of 6 students.
• Please convert your assignment into a PDF file and upload it on Elearning.
• The submission should indicate the names and student numbers of the members
of the group and ONLY one student per group should upload the assignment.
TAKE NOTE:
This assignment is for Full-time and Part-time students ONLY.
1. Given that the resting heart rates of 25 students is given in the following table.
61 63 64 65 65 67 71 72 73 74
75 77 79 80 81 82 83 83 84 85
89 95 95
(a) Construct a 50% confidence interval for the standard deviation of the resting heart rates
for students in this particular class. [10]
(b) Given that the students heart rate of the unknown population variance is claimed to be
no different from 144. Test at 5% that data disagree with the claim. [9]
2. The average prices and quantities of fruits in a certain fixed market for the years 2015 and
2017 were as in the table below.
Fruit 2016 2017
Price/kg (NAD) Quantity (tons) Price/kg (NAD) Quantity (tons)
Orange 18 500 16 600
Banana 15 273 20 317
Strawberry 22 382 27 321
Mango 12 431 18 284
(a) Calculate price index for orange for 2017 with 2016 as base year and interpret it. [2]
(b) Use Paasche’s approach to calculate composite price index for these fruits for 2017 with
2016 as base year and interpret it. [5]
(c) Use Laspeyres’ approach to calculate composite quantity index for these fruits for 2017
with 2016 as base year and interpret it. [5]
3. Consider the following time series data.
Week Day Sales (NAD ‘000’)
1
Mon
Tue
Wed
Thu
Fri
2
4
7
5
4
2
Mon
Tue
Wed
Thu
Fri
7
11
12
10
8
3
Mon
Tue
Wed
Thu
Fri
12
14
15
18
11
(a) Calculate the 4-period moving average sales for these data. [5]
(b) Predict the sales on Friday of the 4th week using OLS trend line with sequentially
coded time, starting with 𝑥 = 3. [7]
(c) Predict the sales on Friday of the 5th week using OLS trend line with zero–sum
coded time. [7]
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