Teaching process is a vital part in the process of knowledge gaining. That is why we put all our affords to create most interactive and breathtaking teaching materials. With our Business Related materials your students will enhance their knowledge and you can be sure that teaching process will be as interesting as it possible.
Teaching process is a vital part in the process of knowledge gaining. That is why we put all our affords to create most interactive and breathtaking teaching materials. With our Business Related materials your students will enhance their knowledge and you can be sure that teaching process will be as interesting as it possible.
Managing the External Environment and the Organization’s Culture is a lecture which is covered during Management Module. This resource is suitable for bachelor and master level students who are studying in business department.
The components of an organization’s culture are as complex as the different aspects of an individual’s personality. Today’s managers must understand how the force of an organization’s internal and external environments may influence, and sometimes constrain, its productivity.
Future Managers must realize that organizational culture and organizational environment have important implications for the way an organization is managed. Both organizational culture and external forces that can shape an organization are explored in order to gain a better under-standing of the complexities presented by internal and external environments.
Learning Objectives of this lecture are:
Contrast the actions of managers according to the omnipotent and symbolic views.
Describe the constraints and challenges facing managers in today’s external environment.
• Develop your skill at scanning the environment so you can anticipate and interpret changes taking place.
Discuss the characteristics and importance of organizational culture.
• Know how to read and assess an organization’s culture.
Describe current issues in organizational culture.
In this file you will find:
1 Managing the External Environment and the Organization’s Culture Lecture Power Point Presentation
1 Lecture Note Guide
1 Test Bank with 116 different questions with full answer description and explanation
8 Interesting Discussion Questions and answers to them
5 Interesting Exercise related to the topic with all answers to them
1 Interesting Case Study with all answers to case study questions
1 additional reading resource file related to lecture topic in order to enhance Lecturer/Teacher/Student knowledge
1 Folder with relevant useful pictures
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All resources are compressed in Zip File.
In this file you will find:
- 1 Lecture Power Point Presentation
- 1 Seminar Power Point Presentation which is linked to Lecture
- 1 Case study with an answer
- Seminar/Lecture Plan
- 1 Seminar group activity task where students need to come up with their own answers
- 2 activities which will help students to understand levels of managers and their main responsibilities.
All materials are used during teaching process for bachelor level student. We already received lots of positive comments regarding the teaching materials.
It is extremely important for teachers / lecturers / tutors to create a nice teaching environment with students. So this files will help you to create really nice introduction for the business course students.
in this file you will find:
- 1 Power Point Presentation for the 1st class/lecture/tutorial/seminar with students of business department or business related modules.
- 1 Tutorial plan with all activities. There are more than 6 different business related ice breaking activities.
In the world of strong competition between the companies it is extremely important for companies to do everything in order to create strong brand and survive in the market. Brand Experience and Experiential marketing are the two tools which will help companies to build a strong brand in the market as well as to increase number of loyal customers.
In this File you will find:
- 1 Brand experience and Experiential Marketing Lecture Power Point Presentation
- 1 Brand experience and Experiential Marketing Seminar Power Point Presentation
- Seminar Plan
- 2 Interactive exercise for the Seminar
- 5 videos and for discussion during Lecture and Tutorials
- Lots of examples of Brand Experience and Experiential Marketing
All provided materials are used for level 5 students of University (Bachelor Level). All provided materials are very interesting and for sure will enhance your students knowledge and skills.
Discrete Probability Distributions is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
This lecture introduces you to the concept and characteristics of probability distributions. Moreover, you will learn how the binomial, Poisson, and hypergeometric distributions can be applied to help solve business problems.
A probability distribution for a discrete variable is a mutually exclusive list of all the possible numerical outcomes along with the probability of occurrence of each outcome. For more information look at the agenda of the lesson.
In this lecture, you learn to:
The properties of a probability distribution
To compute the expected value and variance of a probability distribution
To calculate the covariance and understand its use in finance
To compute probabilities from binomial, hypergeometric, and Poisson distributions
To use the binomial, hypergeometric, and Poisson distributions to solve business problems
In this file you will find:
Discrete Probability Distributions Lecture Power Point Presentation
Test Bank with 171 different related questions with full answer description and explanation
65 Exercises related to the topic with all answers to them
Defining and Collecting Data Reading Resources file in order to enhance Lecturer/Teacher/Student knowledge
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The Normal Distribution and Other Continuous is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
This lecture will help you learn about characteristics of continuous probability distributions and how to use the normal distribution to solve business problems.
In this lecture, you learn to:
To compute probabilities from the normal distribution
How to use the normal distribution to solve business problems
To use the normal probability plot to determine whether a set of data is approximately normally distributed
To compute probabilities from the uniform distribution
To compute probabilities from the exponential distribution
In this file you will find:
The Normal Distribution and Other Continuous Lecture Power Point Presentation
The Normal Distribution and Other Continuous Test Bank with 178 different related questions with full answer description and explanation
53 Exercises related to the topic with all answers to them
The Normal Distribution and Other Continuous Reading Resources file in order to enhance Lecturer/Teacher/Student knowledge
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Sampling Distributions is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
In many applications, you want to make inferences that are based on statistics calculated from samples to estimate the values of population parameters. In this lecture, you will learn about how the sample mean (a statistic) is used to estimate the population mean (a parameter) and how the sample proportion (a statistic) is used to estimate the population proportion (a parameter).
In this lecture, you learn to:
The concept of the sampling distribution
To compute probabilities related to the sample mean and the sample proportion
The importance of the Central Limit Theorem
In this file you will find:
Sampling Distributions Lecture Power Point Presentation
Sampling Distributions Test Bank with 129 different related questions with full answer description and explanation
29 Exercises related to the topic with all answers to them
Sampling Distributions Reading Resources file in order to enhance Lecturer/Teacher/Student knowledge
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Confidence Interval Estimation is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
Suppose you want to estimate the mean GPA of all the students at your university. The mean GPA for all the students is an unknown population mean, denoted by u. You select a sample of students and compute the sample mean, denoted by X, to be 2.80. As a point estimate of the population mean, u, you ask how accurate is the 2.80 value as an estimate of the population mean, u? By considering the variability from sample to sample (see Section 7.2, concerning the sampling distribution of the mean), you can construct a confidence interval estimate for the population mean to answer this question.
When you construct a confidence interval estimate, you indicate the confidence of correctly estimating the value of the population parameter, u. This allows you to say that there is a specified confidence that u is somewhere in the range of numbers defined by the interval. After studying this chapter, you might find that a 95% confidence interval for the mean GPA at your university is 2.75 < u < 2.85. You can interpret this interval estimate by stating that you are 95% confident that the mean GPA at your university is between 2.75 and 2.85.
In this chapter, you learn to construct a confidence interval for both the population mean and population proportion. You also learn how to determine the sample size that is necessary to construct a confidence interval of a desired width.
In this lecture, you learn to:
To construct and interpret confidence interval estimates for the population mean and the population proportion
To determine the sample size necessary to develop a confidence interval for the population mean or population proportion
How to use confidence interval estimates in auditing
When to use a finite population correction factor in calculating a confidence interval for either µ or π
How to use a finite population correction factor in calculating a confidence interval for either µ or π
How to use a finite population correction factor in calculating a sample size for a confidence interval for either µ or π
The concept of bootstrapping and when it makes sense to use it.
In this file you will find:
Confidence Interval Estimation Lecture Power Point Presentation
Confidence Interval Estimation Test Bank with 183 different related questions with full answer description and explanation
68 Exercises related to the topic with all answers to them
Confidence Interval Estimation Reading Resources file in order to enhance Lecturer/Teacher/Student knowledge
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All resources are compressed in zip file.
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Two-Sample Tests is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
In this lecture, you will learn how to extend hypothesis testing to two-sample tests that compare statistics from samples selected from two populations.
Learning objectives:
• How to use hypothesis testing for comparing the difference between
– The means of two independent populations
– The means of two related populations
– The proportions of two independent populations
– The variances of two independent populations
• The impact sample size can have on statistical significance
• How to classify the effect size of a difference
• When it is appropriate to consider the effect size in addition to statistical significance
In this File you will find:
Two-Sample Tests Lecture Power Point Presentation
Test Bank for Two-Sample Tests with 210 Questions with answers
69 Exercises for Two-Sample Tests
Plus reading resource on Two-Sample Tests in order to enhance you overall knowledge about the topic.
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Introduction to Multiple Regression is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
This lecture will introduce you to multiple regression models that use two or more independent variables to predict the value of a dependent variable.
Learning objectives:
• How to develop a multiple regression model
• How to interpret the regression coefficients
• How to determine which independent variables to include in the regression model
• How to determine which independent variables are most important in predicting a dependent variable
• How to use categorical independent variables in a regression model
• How to predict a categorical dependent variable using logistic regression
• How to identify individual observations that may be unduly influencing the multiple regression model
In this File you will find:
Introduction to Multiple Regression Lecture Power Point Presentation
Test Bank for Introduction to Multiple Regression with 343 Questions with all answers to them
86 Exercises for Introduction to Multiple Regression
Plus reading resource on Introduction to Multiple Regression in order to enhance you overall knowledge about the topic.
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Forecasting Test Bank
Forecasting in Operation Management plays a crucial role. That is why it is important for future business managers to have ability and skills which will help them to make at least approximate forecasting. This test bank on Forecasting will help you to assess knowledge of your students.
Entire test is divided into 8 sections, overall there are more than 100 Questions with all answers to them.
There are multiple choice questions, true/false questions, some questions with calculations.
This test bank on Forecasting divided as following:
Section 1 - What is Forecasting? (17 Questions)
Section 2 - The Strategic Importance of Forecasting (1 Question)
Section 3 - Seven Steps in the Forecasting System (5 Questions)
Section 4 - Forecasting Approaches (16 Questions)
Section 5 - Time-Series Forecasting (76 Questions)
Section 6 - Associative Forecasting Methods: Regression and Correlation Analysis (14 Questions)
Section 7 - Monitoring and Controlling Forecasts (10 Questions)
Section 8 - Forecasting in the Service Sector (2 Questions)
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Design of Goods and Services Test Bank
Design of Goods and Services in Operation Management plays a crucial role. That is why it is important for future product or service managers to have proper knowledge and skills which will help them to generate new products and services. This test bank on Design of Goods and Services will help you to assess knowledge of your students.
Entire test is divided into 10 sections, overall there are more than 100 Questions with all answers to them.
There are multiple choice questions, true/false questions, some questions with calculations.
This test bank on Forecasting divided as following:
Section 1 - Goods and Services Selection (25 Questions)
Section 2 - Generating New Products (6 Questions)
Section 3 - Product Development (13 Questions)
Section 4 - Issues for Product Design (19 Questions)
Section 5 - Product Development Continuum (9 Questions)
Section 6 - Defining a Product (10 Questions)
Section 7 - Documents for Production (14 Questions)
Section 8 - Service Design (12 Questions)
Section 9 - Application of Decision Trees to Product Design (12 Questions)
Section 10 - Transition to Production (1 Questions)
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Design of Goods and Services is a lecture which is covered within the Operation Management Module which is covered by Bachelor and Master Level Students.
Learning objectives:
Define product life cycle
Describe a product development system
Build a house of quality
Explain how time-based competition is implemented by OM
Describe how goods and services are defined by OM
Describe the documents needed for production
Explain how the customer participates in the design and delivery of services
Apply decision trees to product issues
In this File you will find:
Design of Goods and Services Lecture Power Point Presentation
Detailed Design of Goods and Services Lesson Plan
Design of Goods and Services Test Bank with answers (more than 100 Questions)
2 Case Studies with all Answers to them and plus 2 videos
18 Discussion Questions for Seminar with Answers
27 Exercises with all answers for Seminar or Lecture
Plus reading resource on Design of Goods and Services in order to enhance you overall knowledge about the topic.
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Operations and Productivity is a lecture which is covered within the Operation Management Module which is covered by Bachelor and Master Level Students.
Operations managers throughout the world are producing products every day to provide for the well-being of society. These products take on a multitude of forms. They may be washing machines at Whirlpool, motion pictures at Dream Works, rides at Disney World, or food at Hard Rock Cafe. These firms produce thousands of complex products every day — to be delivered as the customer ordered them, when the customer wants them, and where the customer wants them.
Learning objectives:
Define operations management
Explain the distinction between goods and services
Explain the difference between production and productivity
Compute single-factor productivity
Compute multifactor productivity
Identify the critical variables in enhancing productivity
In this File you will find:
Operations and Productivity Lecture Power Point Presentation
3 Case Studies with all Answers to them
14 Discussion Questions for Seminar with Answers
17 Exercises with all answers for Seminar or Lecture
Plus reading resource on Operations and Productivity in order to enhance you overall knowledge about the topic.
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Multiple Regression Model Building is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
This lecture discusses multiple regression models with two independent variables. Moreover, this lecture considers regression models that contain more than two independent variables. Also lecture discusses model-building concepts that will help to develop the best model when confronted with a set of data that has many independent variables, such as the data to be collected at WSTA-TV. These concepts include quadratic independent variables, transformations of the dependent or independent variables, stepwise regression, and best-subsets regression.
Learning objectives:
To use quadratic terms in a regression model
To use transformed variables in a regression model
To measure the correlation among the independent variables
To build a regression model using either the stepwise or best-subsets approach
To avoid the pitfalls involved in developing a multiple regression model
In this lecture we discussed:
The quadratic regression model
Using transformations in regression models
- The multiplicative model
- The exponential model
Collinearity
Model building
- Stepwise regression
- Best subsets
The pitfalls & ethical considerations in multiple regression
In this File you will find:
Multiple Regression Model Building Lecture Power Point Presentation
Test Bank for Multiple Regression Model Building with 96 Questions with all answers to them
39 Exercises for Multiple Regression Model Building seminar or lecture
Plus reading resource on Multiple Regression Model Building in order to enhance you overall knowledge about the topic.
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Time-Series Forecasting is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students. A time series is a set of numerical data collected over time. Due to differences in the features of data for various investments described in the Using Statistics scenario, you need to consider several different approaches for forecasting time-series data.
This lecture begins with an introduction to the importance of business forecasting and a description of the components of time-series models. The coverage of forecasting models begins with annual time-series data. First section presents moving averages and exponential smoothing methods for smoothing a series. This is followed by least-squares trend fitting and forecasting in the next section and autoregressive modeling in the following section. After lecture discusses how to choose among alternative forecasting models. Finally lecture develops models for monthly and quarterly time series.
Learning objectives:
To construct different time-series forecasting models: moving averages, exponential smoothing, linear trend, quadratic trend, exponential trend, autoregressive models, and least squares models for seasonal data
To choose the most appropriate time-series forecasting model
In this lecture we discussed:
The importance of forecasting
The component factors of the time-series model
The smoothing of data series
Moving averages
Exponential smoothing
Least square trend fitting and forecasting
Linear, quadratic and exponential models
Autoregressive models
A procedure for choosing appropriate models
Time-series forecasting of monthly or quarterly data by using dummy variables
Pitfalls concerning time-series analysis
In this File you will find:
Time-Series Forecasting Lecture Power Point Presentation
Test Bank for Time-Series Forecasting with 170 Questions with all answers to them
64 Exercises for Time-Series Forecasting seminar or lecture
Plus reading resource on Time-Series Forecasting in order to enhance you overall knowledge about the topic.
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Business Analytics is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
Descriptive analytics, predictive analytics, and prescriptive analytics form the three broad categories of analytic methods. Descriptive analytics explores business activities that have occurred or are occurring in the present moment. Predictive analytics identifies what is likely to occur in the (near) future and finds relationships in data that may not be readily apparent using descriptive analytics. Prescriptive analytics investigates what should occur and prescribes the best course of action for the future. Predictive and prescriptive analytics make practical the use of big data to support decision making, although many of these techniques also work with smaller sets of data, as examples in this chapter demonstrate. This lecture begins with descriptive analytics but focuses on predictive analytics. The lecture does not cover prescriptive analytics methods.
Learning objectives:
To develop dashboard elements such as sparklines, gauges, bullet graphs, and tree-maps for descriptive analytics
How to use classification and regression trees for predictive analytics
How to use neural nets for predictive analytics
How to use cluster analysis for predictive analytics
How to use multidimensional scaling for predictive analytics
In this File you will find:
Business Analytics Lecture Power Point Presentation
Test Bank for Business Analytics with 112 Questions with all answers to them
59 Exercises for Business Analytics seminar or lecture
Plus reading resource on Business Analytics in order to enhance you overall knowledge about the topic.
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A Roadmap for Analyzing Data is a lecture which is covered within the Statistic or Basic Business Statistic module by business and economics students.
Choosing appropriate statistical methods for your data is the single most important task you face and is at the heart of “doing statistics.” But this selection process is also the single most difficult thing you do when applying statistics! How, then, can you ensure that you have made an appropriate choice? By asking a series of questions, you can guide yourself to the appropriate choice of methods.
Learning objectives:
The questions to ask when choosing which statistical methods to use to conduct data analysis
Rules for applying statistics in future studies and analyses
This lecture discusses:
How to choose the appropriate technique(s) for data analysis for both numerical and categorical variables
Potential questions and the associated appropriate techniques for numerical variables
Potential questions and the associated appropriate techniques for categorical variables
In this File you will find:
A Roadmap for Analyzing Data Lecture Power Point Presentation
Test Bank for A Roadmap for Analyzing Data with 327 Questions with all answers to them
15 Exercises for A Roadmap for Analyzing Data seminar or lecture
Plus reading resource on A Roadmap for Analyzing Data in order to enhance you overall knowledge about the topic.
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Project Management is a lecture which is covered within the Operation Management Module which is covered by Bachelor and Master Level Students.
Project management one of the crucial topics in the operation management module. Project management is important for future managers and must to be covered by business students.
Learning objectives:
Use a Gantt chart for scheduling
Draw AOA and AON networks
Complete forward and backward passes for a project
Determine a critical path
Calculate the variance of activity times
Crash a project
In this File you will find:
Project Management Lecture Power Point Presentation
Detailed Project Management Lesson Plan
Project Management Test Bank with answers
4 Case Studies and Videos to them with all Answers to them
18 Discussion Questions for Seminar with Answers
13 Exercises with all answers for Seminar or Lecture
Plus reading resource on Project Management in order to enhance you overall knowledge about the topic.
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Managing Quality (quality management) is a lecture which is covered within the Operation Management Module which is covered by Bachelor and Master Level Students.
Quality, or the lack of quality, affects the entire organization from supplier to customer and from product design to maintenance. Perhaps more important, building an organization that can achieve quality is a demanding task.
LEARNING OBJECTIVES OF LECTURE:
Define quality and TQM
Describe the ISO international quality standards
Explain Six Sigma
Explain how benchmarking is used in TQM
Explain quality robust products and Taguchi concepts
Use the seven tools of TQM
In this file you will find:
• Management Quality Lecture power point presentation
• 4 Case studies with all answers
• 1 Ethical Exercise with answer
• Lecture Notes
• Test Bank with all answers (More than 100 different questions)
Managing Quality Lecture pack will help you to conduct brilliant lecture for your students. Moreover, it contains lots of case studies and exercises which will help you to practice covered materials. Finally, quality management test bank will help you to assess your student knowledge.
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