The paper focuses on the importance of statistics for managers. These are, decision-making in the objective sense, forecasting, planning, organizing, identifying and evaluating alternative courses of action, monitoring processes, and optimizing results, and thriving amidst uncertainty.

Statistics for Managers was defined and digested in terms of the good done the author of this project in terms of capacity-building, analytical-synthesis empowerment, innovation-trending, logical-approaching, appreciation/rigor/strengthening, decision-making and forecasting, and authoring published-texts in the areas of theoretical-physics, economics/management, etc. It is therefore, a diversified area that links-up all fields. It was expatiated as a recipe for managers/graduates that want to dream-big, decide, conclude, and forecast fast on issues, and business, political, social, technological, environmental, or market events. The normal distribution function or subject matter was viewed as everything as far as statistics is the clue. Terms like confidence interval with probabilistic inferences, the null-hypothesis, are helpful in conclusions/recommendations. A typical question from the textbook was digested and excelshowed working on the salient computed values and pasted from excel in appendix here. Space and time limitation of the project demands could not permit the writer to show how the subject could lead to the cognitive power that psychomotor proctored the derivation of the term value into theory, “value science and theory in value mechanics”. This theory is a new theory trending to link general-relativity to quantum mechanics. In fact, statistics for managers is a real booster recommended for everyone.

In this project write-up, I would expatiate briefly on the normal distribution curve and tackle an example problem on regression (r), the null-hypothesis (H0), and the student-t distribution (t) in “one question”, by way of clarifying on the fact that, decisions are needed and conclusions are needed in order to forecast in business, science and technology, and in generally management, and all these are in concernment about what I learned about “statistics for managers”.

Excerpt

Statistics for Managers: Häufig gestellte Fragen (FAQ)

Was ist das Hauptthema des Textes?

Der Text bietet eine umfassende Übersicht über Statistik für Manager, einschließlich Definition, Anwendungsbereiche, wichtiger Konzepte (wie Normalverteilung, Hypothesentests) und praktischer Beispiele. Er betont die Bedeutung von Statistik für fundierte Entscheidungsfindung, Prognosen und strategische Planung in verschiedenen Bereichen, vom Business bis zur Wissenschaft.

Welche Themen werden im Detail behandelt?

Der Text behandelt folgende Themen: Definition und Bedeutung von Statistik für Manager, die Normalverteilung und ihre Anwendungen, deskriptive und inferentielle Statistik, Datentypen, Methoden der Datenerhebung, Hypothesentests (dargestellt am Beispiel eines Korrelationstests), und die Anwendung statistischer Methoden zur Entscheidungsfindung in Unternehmen.

Welche konkreten Beispiele werden im Text verwendet?

Ein konkretes Beispiel aus dem Lehrbuch "Business Statistics" von Groebner et al. (2008) wird Schritt für Schritt durchgearbeitet. Es geht um die Untersuchung der Korrelation zwischen der Größe von Anzeigen in einem Telefonbuch und der Anzahl der daraus resultierenden Anrufe. Die Lösung beinhaltet die Formulierung von Hypothesen, die Berechnung des Korrelationskoeffizienten und die Durchführung eines t-Tests.

Welche Schlussfolgerungen zieht der Autor?

Der Autor betont die weitreichende Bedeutung von Statistik für Manager in allen Bereichen des Lebens und Wirtschaftens. Statistik ermöglicht fundierte Entscheidungen, Prognosen und die Bewältigung von Unsicherheiten. Der Autor beschreibt auch seine persönlichen Erfahrungen und wie Statistik seine Karriere positiv beeinflusst hat.

Welche weiterführenden Literaturquellen werden empfohlen?

Der Text enthält eine Liste empfohlener Literatur, darunter Lehrbücher zur Managementwissenschaft und Statistik, sowie Links zu Online-Ressourcen und eigenen Veröffentlichungen des Autors.

Wie ist der Text aufgebaut?

Der Text ist übersichtlich strukturiert mit einem Inhaltsverzeichnis, einer Zusammenfassung (Abstract), einer Einleitung, Abschnitten zu den einzelnen Themen, einem Schlussteil, einer Literaturliste und einem Anhang mit zusätzlichen Informationen.

Für wen ist dieser Text gedacht?

Der Text richtet sich an Manager, Studenten der Wirtschaftswissenschaften und alle, die sich für die Anwendung statistischer Methoden in der Praxis interessieren. Der Text ist sowohl für Anfänger als auch für Fortgeschrittene geeignet.

Wo finde ich mehr Informationen zum Autor und seinen weiteren Arbeiten?

Der Text enthält Links zu den Webseiten des Autors, wo weitere Informationen zu seinen Veröffentlichungen, seiner Organisation "Bacorg University" und seinen Forschungsprojekten gefunden werden können. Die Arbeiten des Autors scheinen sich auch auf die Entwicklung von "Value Mechanics" zu konzentrieren.

Welche Software wird im Text erwähnt?

Der Text erwähnt verschiedene Software-Tools, die in der statistischen Datenanalyse und im Management eingesetzt werden können, darunter MATLAB, Minitab, LINDO/LINGO, Decision-Trees, ORACLE und MS Excel.

Gibt es einen Anhang?

Ja, der Text enthält einen Anhang, der in diesem Auszug jedoch nicht vollständig angezeigt wird. Es wird angedeutet, dass dieser Anhang detaillierte Berechnungen und Excel-Tabellen enthält.

ABSTRACT

INTRODUCTION

THE NORMAL DISTRIBUTION

ABOUT STATISTICS FOR MANAGERS IN GENERAL

FOR EXAMPLE - SOURCE: GROEBNA ET AL (2008). BUSINESS STATISTICS: A DECISION-MAKING APPROACH

CONCLUSION

ABSTRACT

Statistics for Managers was defined and digested in terms of the good done the author of this project in terms of capacity-building, analytical-synthesis empowerment, innovation-trending, logical-approaching, appreciation/rigor/strengthening, decision-making and forecasting, and authoring published-texts in the areas of theoretical-physics, economics/management, etc. It is therefore, a diversified area that links-up all fields. It was expatiated as a recipe for managers/graduates that want to dream-big, decide, conclude, and forecast fast on issues, and business, political, social, technological, environmental, or market events. The normal distribution function or subject matter was viewed as everything as far as statistics is the clue. Terms like confidence interval with probabilistic inferences, the null-hypothesis, are helpful in conclusions/recommendations. A typical question from the textbook was digested and excel-showed working on the salient computed values and pasted from excel in appendix here. Space and time limitation of the project demands could not permit the writer to show how the subject could lead to the cognitive power that psychomotor proctored the derivation of the term value into theory, “value science and theory in value mechanics”. This theory is a new theory trending to link general-relativity to quantum mechanics. In fact, statistics for managers is a real booster recommended for everyone.

INTRODUCTION

Statistics for managers is simply an advanced level statistic and it finds application in all systems especially in business and organizations, also, because, “almost all entities are managed” and it is a modern style for managers of entities to be empowered with such a tool. It is therefore, a subject, a course, or a statistically methodologically styled science which is approached by managers especially, in managing businesses or organizations, and which leverages modern style management to the scientific level and manner, for instance as in the program “management science”, strategic management, marketing management, project management and more, and of which data is organized and changed into meaningful information. Since statistics for managers finds a great application in business it is sometimes referred to in business as business statistics. Business statistics is therefore, “a set of tools that are used to transform data into information” (Groebner et al, 2008)¹. Among the most relevant data collection tools and methods are; experimentation, telephone surveys, written questionnaire surveys, direct observation and personal interviews, Groebner et al (2800). In business programs students study statistics for managers and I studying it at the MBA level, I must say that, it tremendously changed my life as a data analyzer coupled with decision making in diverse ways in management. As a result, I became an author of published books² which in this way focused the positive impact that I in turn made on the environment, and as a benefit to the academic sphere and therefore, additions to the bodies of knowledge already existing. It further, helped me become an establisher of an organization i.e. “Bacorg University”³, also, from the power of data analysis due to this subject, I became an innovator and a discoverer of an algorithm known as the “model of universality of value: (b+v ≤ u+s) where, b is “basic”, v is “value”, u is “valuable”, and s is “slack” which led to the innovation of a mechanics known as ‘value mechanics’”⁴. The idea was based on enhancing anything of a system which is dubbed a ‘valuable’, and, “the level of the valuable is proportional to the magnitude of the value”⁵. Statistics for managers also, empowered me to lecture in the university czu.cz⁶, and it is the confidence which motivated me to undertake a PhD in Information Technology and Management⁷. With this far, statistics for managers was the initiative, and as stated earlier, it is not only for business field but it finds wide applications in all fields including the natural sciences i.e. physics, chemistry, biology, agriculture, psychology, philosophy, geography, etc.

In general, what I learned about statistics for managers focused on the importance of statistics for managers. These are, decision making in the objective sense, forecasting, planning, organizing, identifying and evaluating alternative courses of action, monitoring processes, and optimizing results, and thriving amidst uncertainty, that is, “the only certainty about the future is its “uncertainty””, (Dr. Veena K. N. 2014)⁸. In general, a learner is empowered by the subject in direct resolution to problems of systems and in business through a consistent system of presenting concepts and techniques, and incapacitates professionals to demonstrate powerful decision making prowess in today’s business and other management systems. Two broad methods of statistics exist, descriptive statistics (about a system or population, it utilizes data to make descriptions by numerically computations, by tabulation, or graphically) and inferential statistics (about a system or population, it leverages inferences and forecasts depending on a data sample obtained from the system), and generally, there are four types of data namely quantitative (numerical data: e.g. percentages, dollars, pounds, inches, number of hours work, etc.), qualitative (categorical data: classifying ranks, e.g. senior, junior), cross-sectional (data relating to a fixed point in time, e.g. 250 stocks could be sampled and the price determined on a fixed date), and time-series (data values observed at intervals of time, e.g. tracking sales figures of iphones by Apple at weekly intervals), and with these, are connected the importance of statistics and the content and this whole content could be found in the book, “Business Statistics by Groebner et al, 2008”.

In this project write-up, I would expatiate briefly on the normal distribution curve and tackle an example problem on regression (r), the null-hypothesis (H0), and the student-t distribution (t) in “one question”, by way of clarifying on the fact that, decisions are needed and conclusions are needed in order to forecast in business, science and technology, and in generally management, and all these are in concernment about what I learned about “statistics for managers”.

THE NORMAL DISTRIBUTION

The normal distribution is everything upon all the statistical rigor to whatever level that one may consider an uncertainty. To me the normal distribution represents even the whole universe and the analysis of everything that exists, existed, and will exist. The theory of universality is simply as well as the normal distribution when we break it down, and requires statistics in the rigorous sense to break it down completely in order to acquire its aspiring abstract mechanics projected someday. Everything that is iterated continuously as a real-valued randomized variable as probabilities will assume a state of normal distribution and this agrees with the model of universality which has to do with enhancing a system iteratively. The normal distribution is a continuous probability distribution of a real-valued random variable and whose probability density function is given by f(x) = {1-0.5[(x-µ)Λ2/σ]}/σ√2, where, σ is standard deviation, σ2 is variance, µ is mean, the distribution expectation, the median, or mode⁹.

The normal distribution finds quite a wide application in real-valued randomized variables whose distributions are not known but its importance remains partly due to the central limit theorem (CLT). CLT hence, “establishes that, in some situations, when independent random variable is added, their property normalized sum tends to a normal distribution, even if the original variable themselves are not normally distributed. This means probabilistic and statistic methods that work for normal distribution can be applicable to many problems”¹⁰. There are different forms of the normal distribution such as the standard normal distribution (the simplest), the general normal distribution, the student t-distribution which finds application where we estimate the mean of normal distribution population with a small sample size coupled with unknown standard deviation, the logistic distribution which is normal distribution but heavier tails or kurtosis, and the Cauchy distribution whose expected value and variance are undefined continuous, also, Levy-distribution which is a probability distribution for a non-negative variable. The shape of the normal distribution is a bell-shape and can skew

ABOUT STATISTICS FOR MANAGERS IN GENERAL

Statistics for managers, it’s a subject that incapacitates envisaged to anticipate the success or not of a business, a system, an entity, or an organization if established. Usually, there is a need to fetch a niche from the market or the industry in concernment, map out the target group for the products or services to be ventured, in this case design an appropriate questionnaire, conduct telephone survey or personal interviews with the designed questionnaire, survey through emails or online survey tools through platforms such as, “SurveyMonkey, Smart Survey, Survey Gizmo, Survey Planet, Zoho Survey, Client Heartbeat (paid online survey tool), Google Forms, Typeform, ProProfs Survey Maker, SoGoSurvey” (Megan Marrs, 2020)¹¹, and this is by way of data collection, organizing or processing data, analyzing the data by ANOVA, by regression analysis, interpreting data, and making meaning out of it to the understanding of even the lame man, and using the refined data to make decisions, decisions could be administered through the null hypothesis or extending the refined data through management science i.e. “quantitative studies of management decision making” to make decisions that steers an entity in the right or probabilistic direction. Statistics for managers is a powerful cutting-edge tool formerly embraced on the general today which combines business statistics with quantitative studies in business decision making to do technological wonders. One even gets empowered to be able to program and develop models that lead to quantitative analysis i.e. sensitivity analysis and onward decision making in business, weather forecasting, in flood insurgence, in anticipating the most probable time, extent of damage, and area to be covered by hurricane, tsunami, etc. and leads to forestalling preparations to counter or escape before the unexpected circumstance could set in. That is, “statistics for managers is a very broad arm that combines almost all the statistical methods, and books, and such accompanying software such as MATLAB, Minitab, LINDO/LINGO, Decision-trees, ORACLE, EXCEL types, MS Excel, etc. into fast tabulation techniques and quantifications, and even qualitative analysis for fast decision making that moves-on an entity up the gradient of strategic development, and in taking cutting edge technological strands”, into success. Statistics for managers is used by the military, in science and technology as spelt out earlier, in economics and econometrics, in agriculture as stated before, in medicine, by astronauts, by astronomers, in space science, in manufacturing as stated earlier, in software developments, in deep-water engineering, building gigantic bridges in civil engineering, telephony service targeted area coverage, in computer engineering, in software engineering, and as stated earlier in business generally.

FOR EXAMPLE - SOURCE: GROEBNA ET AL (2008). BUSINESS STATISTICS: A DECISION-MAKING APPROACH

If a regional telephone book publisher by means of a simple random survey wanted to determine whether the size of the company’s advertisement in square inches (x) of the books 10 commercial yellow-pages advertising-customers, “correlated-positively,” with the proportion of calls to the businesses due to the advertisements (y), then, later in one-month period, each commercial-customer asked each caller to their business, did you learn about our business through the yellow pages? This is a problem of which we could determine whether there is a statistically significant correlation between the two variables. We could use the ff steps:

1. Specify the population parameter of interest: The parameter of interest is the “population correlation, ρ”
2. Formulate the appropriate null and alternative hypotheses: The interest is to establish a positive correlation between size and proportion of calls due the advisements (the test is then one-tailed: i.e. “H0: ρ ≤ 0”, “HA: ρ > 0”)
3. Specify the level of significance: A significant level of 0.05 is chosen
4. Compute the correlation coefficient and the test statistics: We find the sample correlation coefficient¹² using the equations = 0.7796 , and t = r = r/√[(1-r2)/(n-2)] = 0.7796/√[(1- 0.77962)/(10-2)] = 3.52, where, t = number of standard errors r is from 0, r = sample correlation coefficient, and n = sample size. The following sample data were obtained:
5. Construct the rejection region and decision rule: For 0.05 level of alpha, we got a one tailed diagram of upper-tail and since n-2 = 10 – 2 = 8 degrees of freedom we calculate t0.05 = 1.8595 by the t values, and the decision rule as follows: If t > 1.8595, reject the null hypothesis. Otherwise do not reject it.
6. Reach a decision: Since t = 3.52 > 1.8595, reject the null hypothesis
7. Draw a conclusion: The rejection of the sample data implies that it supports the contention that there is a positive correlation or linear link between the advertisement size and the proportion of calls that were generated by the advertisements.

CONCLUSION

Now we can see from the resolution of the above question that a problem was statistically deduced first of all by data processing through data collection, data organization, analysis and interpretations, computations, and a decision is reached and based on it a conclusion is drawn and a forecast or prediction done. Predictions or forecasts could be leveraged for a diversified array of issues and events and not only for ads size in correlation with call proportions made. We could forecast the weather which of cause we view every day on our Telis, flooding, crack propagations, earth quakes, tsunamis, hurricanes, market crunches, global recessions, population trends, or political election voting outcomes, etc. and this is what “statistics for managers” can do, this is the power imbibed in it. A whole country is ran successfully based on the power of Statistics for Managers, it is a powerful recommendation for all graduate students, and managers of corporates, and financial ministries, or other ministries or departments in a country in education, in health, in information, in trades and industries, in housing, in energy supplies, name them.

APPENDIX

Abbildung in dieser Leseprobe nicht enthalten

[...]

¹ Groebner et al (2008). Business Statistics. A Decision-Making Approach. Seventh Edition. New Jersey. Prentice Hall

² LINK: https://www.bacorg.com/?page_id=267 (at this blog page of Bacorg University I wrote an article which is making a global impact and the titles of all my books are listed here including their respective links)

³ Dornyo (2015). Bacorg University was established in 2015, however, we are not yet running as a full fledge university, we are still in the establishment process. URL: https//www.bacorg.com (I built this website on my own and improvements are still ongoing)

⁴ Dornyo (2020). Forerunning Value Mechanics in Value Science and Theory 2 and 3. (B+V≤U+S). The Discovery, Verification, and Justification of the Model of Universality of Value and its Sensitivity. LINK: https://www.amazon.com/s?k=forerunning+value+mechanics&crid=JJXJ6WM9Y1TT&sprefix=forerunning%2Caps%2C249&ref=nb_sb_ss_i_1_11 (There are two other books here and they were all written by me).

⁵ Page 8. Forerunning Value Mechanics. The Model Of The Universe Of Values. The Doctoral Dissertation That Led To The Value Science And Theory.: LINK: https://www.book-ebooks.com/forerunning-value-mechanics-the-model-of-the-universe-of-values-13720454.html OR https://www.barnesandnoble.com/w/forerunning-value-mechanics-the-model-of-the-universe-of-values-wisdom-yao-dornyo/1136518553

⁶ LINK: https://www.czu.cz/cs/ (I briefly lectured economics and management related courses in this university in the year 2013 when I was a second year distant doctoral student in AIU)

⁷ I pursued the above-mentioned distant study program for four years into the fifth year i.e. from 2012 to 2017 in AIU which is accredited by a British accreditation “ASIC”. LINK: https://www.aiu.edu/

⁸ Dr. Veena (2014). The importance of Statistics for Managers. Dated visited the website: July 25, 2020. Website: https://iba.ac.in/statistics-for-managers/

⁹ Wikipedia.org (2020). The Normal Distribution. Date visited the website: July 27, 2020. LINK: https://en.wikipedia.org/wiki/Normal_distribution

¹⁰ Encyclopedia Britannica. Date visited the url: August 12, 2020. Url: https://www.britannica.com/science/central-limit-theorem OR Recommended reading also from, wikipedia.org. Date visited the url: August 12, 2020, Url: https://en.wikipedia.org/wiki/Central_limit_theorem

¹¹ Megan Marrs (2020). 9 Best Survey Tools: Create Awesome Survey for Free! Date visited the website: August 2, 2020. Website: WordStream.com LINK: https://www.wordstream.com/blog/ws/2014/11/10/best-online-survey-tools

¹² See appendix for my detailed break down and excel approach to how the 0.7796 was obtained. The work was self-explanatory

Excerpt out of 11 pages - scroll top

Details

Title: The Importance of Statistics for Managers
Course: STATISTICS
Grade: A
Author: Wisdom Yao Dornyo (Author)
Publication Year: 2020
Pages: 11
Catalog Number: V922057
ISBN (eBook): 9783346231482
Language: English
Tags: importance statistics managers
Product Safety: GRIN Publishing GmbH

Quote paper: Wisdom Yao Dornyo (Author), 2020, The Importance of Statistics for Managers, Munich, GRIN Verlag, https://www.hausarbeiten.de/document/922057

The Importance of Statistics for Managers

Excerpt

Statistics for Managers: Häufig gestellte Fragen (FAQ)

Was ist das Hauptthema des Textes?

Welche Themen werden im Detail behandelt?

Welche konkreten Beispiele werden im Text verwendet?

Welche Schlussfolgerungen zieht der Autor?

Welche weiterführenden Literaturquellen werden empfohlen?

Wie ist der Text aufgebaut?

Für wen ist dieser Text gedacht?

Wo finde ich mehr Informationen zum Autor und seinen weiteren Arbeiten?

Welche Software wird im Text erwähnt?

Gibt es einen Anhang?

TABLE OF CONTENTS

ABSTRACT

INTRODUCTION

THE NORMAL DISTRIBUTION

ABOUT STATISTICS FOR MANAGERS IN GENERAL

FOR EXAMPLE - SOURCE: GROEBNA ET AL (2008). BUSINESS STATISTICS: A DECISION-MAKING APPROACH

CONCLUSION

RECOMMENDED READINGS

APPENDIX

Details