Topic 2 Tutorial Solutions
PREPARE BEFORE CLASS
1. Ch 19, page 856, Exercise 19.2.
The asset section of the statement of financial position and notes thereto of Megabus
Ltd is shown below:
Cash assets
Receivables
Inventories
Prepaid insurance
Furniture an
Accounting Concepts and Methods
Measurement of profit; Income statement;
Statement of Cash Flows; and
Analysis and interpretation of the statements
Assessments updates
Research assignment:
Week 3: Groups are finalised in tutorial classes this week;
Wee
Accounting Concepts and Methods (M)
Overview
THE UNIVERSITY OF ADELAIDE
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BUSINESS SCHOOL
MASTERS PROGRAMS
ACCTING 7019 ACCOUNTING CONCEPTS AND METHODS (M)
Topic 1:
Overview of Accounting:
Accounting process, decision making process, regulatory
Accounting Concepts and Methods (M)
Statement of financial position
THE UNIVERSITY OF ADELAIDE
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BUSINESS SCHOOL
MASTERS PROGRAMS
ACCTING 7019 ACCOUNTING CONCEPTS AND METHODS (M)
Topic 2:
Balance sheet (Statement of financial position);
Introdu
60.
The degrees of freedom error (within group variation) of a completely randomized design
(one-way) ANOVA test with 4 groups and 15 observations per each group is:
56
Feedback: Error df = n - treatment levels = 60 - 4 = 56
AACSB: Analytic
Blooms: Applic
Topic: One-way ANOVA
106.
Suppose you are a researcher investigating the annual sales differences among five categories
of businesses. Looking at a total of 55 companies equally divided among categories groups A,
B, C, D, and E.
Is there a significant dif
Learning Objective: 11-02 Compare several different population means by using a one-way analysis of variance.
Topic: One-way ANOVA
73.
Consider the randomized block design with 4 blocks and 3 treatments given above.
What are the degrees of freedom for tre
73.
Regression Analysis
The local grocery store wants to predict the daily sales in dollars. The manager believes that
the amount of newspaper advertising significantly affects the store sales. He randomly selects
7 days of data consisting of daily grocer
100.
A local tire dealer wants to predict the number of tires sold each month. He believes that the
number of tires sold is a linear function of the amount of money invested in advertising. He
randomly selects 6 months of data consisting of tire sales (in
81.
An experiment was performed on a certain metal to determine if the strength is a function of
heating time. Results based on 10 metal sheets are given below. Use the simple linear
regression model.
= 30
= 104
= 40
= 178
= 134
Find the t statistic and t
85.
An experiment was performed on a certain metal to determine if the strength is a function of
heating time. The simple linear regression equation is
= 1 + 1X. The time is in minutes and
the strength is measured in pounds per square inch.
The 95% confid
63.
The _ is the proportion of the total variation in the dependent variable
explained by the regression model.
A. Coefficient of determination
B. Correlation coefficient
C. Slope
D. Standard error
AACSB: Reflective Thinking
Blooms: Knowledge
Bowerman - C
65. The following results were obtained from a simple regression analysis:
= 37.2895 - (1.2024)X
r2= .6744 sb= .2934
For each unit change in X (independent variable), the estimated change in Y (dependent variable)
is equal to:
66. The following results we
140.
Consider the following partial computer output from a simple linear regression analysis.
S = 0.4862 R-Sq = 0.7286
Analysis of Variance
What is the correlation coefficient?
-0.8536
Feedback: r2 = Explained variance/Total variance = 8.251/11.324 = .728
123.Consider the following partial computer output from a simple linear regression analysis.
Write the equation of the least squares line.
124.Consider the following partial computer output from a simple linear regression analysis.
Test H0:1 0 vs. Ha: 1>
116.
A data set with 7 observations yielded the following. Use the simple linear regression model.
= 21.57
= 68.31
= 188.9
= 5,140.23
= 590.83
SSE = 1.06
Find the rejection point for the t statistic (
= .05). Test H0: 1 0 vs. Ha: 1 > 0.
13.993, reject nul
Learning Objective: 13-01 Explain the simple linear regression model.
Topic: Simple Linear Regression
121.
Consider the following partial computer output from a simple linear regression analysis.
What is the estimated y-intercept?
-28.13
AACSB: Analytic
B
Blooms: Application
Bowerman - Chapter 13 #134
Difficulty: Easy
Learning Objective: 13-01 Explain the simple linear regression model.
Topic: Simple Linear Regression
135.
Consider the following partial computer output from a simple linear regression analy
74. Regression Analysis
The local grocery store wants to predict the daily sales in dollars. The manager believes that the
amount of newspaper advertising significantly affects the store sales. He randomly selects 7 days
of data consisting of daily grocer
112.
A local tire dealer wants to predict the number of tires sold each month. He believes that the
number of tires sold is a linear function of the amount of money invested in advertising. He
randomly selects 6 months of data consisting of monthly tire s
96. A local tire dealer wants to predict the number of tires sold each month. He believes that the
number of tires sold is a linear function of the amount of money invested in advertising. He
randomly selects 6 months of data consisting of tire sales (in
77.
An experiment was performed on a certain metal to determine if the strength is a function of
heating time. Results based on 10 metal sheets are given below. Use the simple linear
regression model.
= 30
= 104
= 40
= 178
= 134
Find the estimated y inter
96.
A local tire dealer wants to predict the number of tires sold each month. He believes that the
number of tires sold is a linear function of the amount of money invested in advertising. He
randomly selects 6 months of data consisting of tire sales (in
139.Consider the following partial computer output from a simple linear regression analysis.
S = 0.4862 R-Sq = _
Analysis of Variance
What is the coefficient of determination?
140.Consider the following partial computer output from a simple linear regress
108.
A local tire dealer wants to predict the number of tires sold each month. He believes that the
number of tires sold is a linear function of the amount of money invested in advertising. He
randomly selects 6 months of data consisting of tire sales (in
80. An experiment was performed on a certain metal to determine if the strength is a function of
heating time. Results based on 10 metal sheets are given below. Use the simple linear regression
model.
= 30
= 104
= 40
= 178
= 134
Determine the standard err
131.Consider the following partial computer output from a simple linear regression analysis.
S = 0.4862 R-Sq = _
Analysis of Variance
Write the equation of the least squares line.
132.Consider the following partial computer output from a simple linear reg
69.
Regression Analysis
The local grocery store wants to predict the daily sales in dollars. The manager believes that
the amount of newspaper advertising significantly affects the store sales. He randomly selects
7 days of data consisting of daily grocer
90.
An experiment was performed on a certain metal to determine if the strength is a function of
heating time. Partial results based on a sample of 10 metal sheets are given below. The simple
linear regression equation is
= 1 + 1X. The time is in minutes
144.
The following time sequenced observations of actual and predicted values of the dependent
variable (demand) are obtained from a simple regression model. Determine the Durbin-Watson
statistic (d).
1.889
Feedback: ei2 = 18 (ei - ei-1)2 = 34
d = 34/18 =