Chapter 1
1. Statistics is the science of collecting, organizing, analyzing, interpreting, and presenting data. TRUE 2. Inferential statistics refers to generalizing from a sample to a population, estimating unknown parameters, drawing conclusions, and making decisions. TRUE

3. Descriptive statistics refers to summarizing data rather than generalizing about the population. FALSE
4. Estimating parameters and testing hypotheses are important aspects of descriptive statistics. FALSE
5. Inconsistent treatment of data by a researcher is a symptom of poor survey or research design. FALSE
6. Empirical data are collected through observations and/or experiments. TRUE
7. Business intelligence refers to collecting, storing, accessing, and analyzing data on the company's operations in order to make better business decisions. TRUE
8. When a statistician omits data contrary to her findings in a study, she is justified as long as the sample supports her objective. FALSE
9. A strong correlation between A and B would imply that B is caused by A. FALSE
10. The post hoc fallacy says that when B follows A then B is caused by A. TRUE
11. A statistical test may be significant yet have no practical importance. True False
12. Valid statistical inferences cannot be made when sample sizes are small. TRUE
13. Statistics is an essential part of critical thinking, because it allows us to transform the empirical evidence from a sample so it will agree with our preferred conclusions. TRUE
14. Statistical challenges include imperfect data, practical constraints, and ethical dilemmas. TRUE
15. A business data analyst needs a PhD in statistics.
FALSE
16. The science of statistics tells us whether the sample evidence is convincing. True False
17. Pitfalls to consider in a statistical test include non-random samples, small sample size, and lack of causal links. TRUE
18. In business communication,...

...9.54
(a) At the .01 level of significance,is the true mean greater than 10?
Null Hypothesis: Ho: M = 10 :Mean is 10 or less pages
Alternative Hypothesis: H1: M >10 :Mean is more than 10 pages
Significance level=alpha (a) = 0.01 or 1%
No of tails= 1
This is a 1-tailed test because we are testing that the mean is greater than 10
Since sample size= 35 >= 30
we will use normal distribution
This is a one tailed test because we are testing the area in the right tail
Since the sample size is large we will use z distribution
Z at the 0.01 level of significance 1 tailed test = 2.3263
z critical= 2.3263
Decision rule
If the sample z value > z critical, 2.3263 reject Null Hypothesis
If the sample z value < z critical , 2.3263 accept Null Hypothesis
Alternatively:
If p value < significance level , 0.01 reject Null Hypothesis
If p value > significance level , 0.01 accept Null Hypothesis
Hypothesized Mean=M = 10 pages
Standard deviation =s= 4.45 pages
sample size=n= 35
sx=standard error of mean=s/square root of n= 0.7522 = ( 4.45 /square root of 35)
sample mean= 14.44 pages
z=(sample mean-M )/sx= 5.9027 =(14.44-10)/0.7522
Reject Null Hypothesis since z> z critical
The mean is greater than 10 pages
9.56
Null Hypothesis:Ho: p = 50.%
Alternative Hypothesis:H1: p > 50.%
Level of significance=alpha (a) = 0.10 or 10.0%
This is a one...

...Table of Contents
1. INTRODUCTION
2. MAIN BODY
2.1 THE NATURE OF RESOURCE COST STRUCTURE AND THE PRACTICAL SIGNIFICANCE OF DIFFERENT COSTS
2.2 THE FACTORS INFLUENCING OPTIMUM SIZE AND THE SIGNIFICANCE OF DEMAND AND SUPPLY RELATIONSHIPS
2.3 UNDERSTANDING OF THE RELEVANCE AND LIMITATIONS OF ECONOMIC THEORY TO MANAGE DECISIONS
3. CONCLUSION
1. INTRODUCTION:
From the economic perspective, there are a full range of wants from individuals, firms and government but there is only a few number of resources or factors of production such as land, labour, capital and enterprise. The raw material will come from land, taking the example of oil, gas. The labour relates to the individuals able to work. The capital covers machinery, computers, offices or shops for retail people. Enterprise will bring all of these factors together and allow them to produce goods and services in order to make a profit. This individual report will be identifying the nature of resource cost structure and the practical significance of different cost. It will also explain the factors influencing optimum size and the significance of demand and supply relationships. It will finally demonstrate an understanding of the relevance and limitations of economic theory to management decisions.
2. MAIN BODY:
2.1 ECONOMIC PERSPECTIVE IN ORDER TO RUN THE COMPANY EFFICIENTLY:
Considering an example of project of...

...result of their success in maximising sales. They will now also have an increased market share.
Profit Maximisation
Profit is the return received on a business undertaking after all their charges/expenses have been paid
Below we can see Sainsbury’s profit data over a 5 year period.
Over 5 years, Sainsbury’s profit has increased by 23.9%
For Sainsbury’s’ profit to increase, they have clearly worked hard to increase their market share and additionally to increase their sales. This has resulted in their profits to increase. They may have also cut certain costs when it comes to packaging, logistics, supplier’s costs etc. For Sainsbury’s, increasing their profits is absolutely paramount for them – and probably their biggest goal/objective. It means they can then go on to make more profit through different ways, such as opening new stores, investing money into current stores for refurbishments which would make the shop a more attractive prospect for customers. They could drive more money into their website, to make it even more accessible for customers. As far as a company like Sainsbury’s is concerned – there is always room for improvement.
Market Share
Definition of market share is the share of total sales secured by one particular shop or company
The formula to calculate market share is to;
1. Calculate your company's total revenue (also called total sales).
2. Calculate the total market sales.
3. Divide your...

...Statistics is the study of the collection, organization, analysis, interpretation, and presentation of data. It deals with all aspects of this, including the planning of data collection in terms of the design ofsurveys and experiments.
The word statistics, when referring to the scientific discipline, is singular, as in "Statistics is an art “This should not be confused with the word statistic, referring to a quantity (such as mean or median) calculated from a set of data, whose plural is statistics ("this statistic seems wrong" or "these statistics are misleading").
-------------------------------------------------
Scope
Some consider statistics a mathematical body of science that pertains to the collection, analysis, interpretation or explanation, and presentation of data while others consider it a branch of mathematics]concerned with collecting and interpreting data. Because of its empirical roots and its focus on applications, statistics is usually considered a distinct mathematical science rather than a branch of mathematics. Much of statistics is non-mathematical: ensuring that data collection is undertaken in a way that produces valid conclusions; coding and archiving data so that information is retained and made useful for international comparisons of official statistics; reporting of results and summarised...

...CH. 1 Why the Social Researcher Uses Statistics?
The Nature of Social Research
• Social scientists attempt to explain and predict human behavior
– Social scientists uses scientific methods to study the social world: human behaviors & interactions
– Variables: characteristics that differ or vary from one individual to another or from one point in time to another
• Ex. Age, social class, and attitude or unemployment, crime rate and population
– Constants: characteristics that do not vary
• Ex. The gender of the person who gave birth to you is female. Thus, in any group of individuals, gender of mother is the constants ‘female’ and does not change
– Unit of observation- what are we measuring?
• Measuring the individual & comparing individuals
– Aggregates – how measures vary across entire collections of people
– Hypotheses- usually a statement about the relationship between two or more variables
• Independent variable- presumed cause; causing a change in the other
• Dependent variable- presumed effect; being influence, affected or changed
• Ex. Education vs. income; the better the education(independent variable) the greater the income (dependent variable)
Why Test Hypotheses?
• Common sense vs. social science research
– Common sense: observation are generally based on narrow, often biased preconceptions & personal experiences; can be misled by assumptions & stereotypes
– Social science research: scientific...

...INTRODUCTION
Statistics and mathematics are everything to economics. infact statistics and Mathematics, the economic field wouldn't even exist.
Economist need statistics to represent data, to track and store information, to identify trends, to attribute value and mathematics to calculate those figures.The way to look at the relationship between statistics and economics is thateconomics is essentially the study of human decisions and trends, and how these have a financial impact.
Economists rely on information to form analyses, understanding and opinion on the human activity that they are scrutinizing. This information comes in the form of statistical data.
Statistics is the core around which economic deductions are built. It highlights the relationship between figures that would otherwise be meaningless, and is key to economic analysis.
An example of this would be an economist trying to analyze the performance of a car manufacturer over the period of a year.
Figures that show the car manufacturer's sales, profits, costs, and other important economic information would be relayed through the use of statistics.
Although people would be right to argue that economics requires more than just statistics (for example, it also relies heavily on understanding...

...In today’s world, we are faced with situations everyday where Statistics can be applied. In general, Statistics is the science of collecting, organizing, and analyzing numerical data. The techniques involved in Statistics are important for the work of many professions, thus the proper preparation and theoretical background of Statistics is valuable for many successful career paths. Marketing campaigns, the realm of gambling, professional sports, the world of business and economics, the political domain, education, and forecasting future occurrences are all areas which fundamentally rely on the use of Statistics. Statistics is a broad subject that branches off into several categories. In particular, Inferential Statistics contains two central topics: estimation theory and hypothesis testing.
The goal of estimation theory is to arrive at an estimator of a parameter that can be implemented into one’s research. In order to achieve this estimator, statisticians must first determine a model that incorporates the process being studied. Once the model is determined, statisticians must find any limitations placed upon an estimator. These limitations can be found through the Cramer-Rao lower bound. Under smoothness conditions, the Cramer-Rao lower bound gives a formula for the lower bound on the variance of an unbiased estimator. Once the...

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