Distinguish between primary data and secondary data? Primary data is the data that is collected first hand from the original source for the purpose of making statistical inference while secondary data is the data that is collected by the method of abstraction and is used to make statistical inference by using primary data already collected by an investigator. Primary data is collected by Identifying population of interest choosing sample analyse sample information draw inference from
Premium Question Interrogative word Sentence
s= = x-x2n-1 | Q1n+14‚ Q7+14=84=2postion Q3=3(n+1)4=3(7+1)4=244=6‚ IQR Q3-Q1‚ | CV=sx×1003.297×100%=47%/ n = 5 has a mean of 10.2.four data: 9‚ 10‚ 8 17‚ find the missing data value.x=i=1nxin=8+9+10+17+?5=*5=10.2‚ 5×10.2=51 Therefore: 8+9+10+17+?=51Therefore: 8+9+10+17+?=51Simplifying: 44+?=51And so ?=51-44=7Thus the missing data value is 7. | Variance/s2= x-x2n-1‚ [3-72+4-72+7-72+7-72+9-72+12-72]6-1 =545 =10.8 | egA manufacturer of insulation randomly selects 20 winter days
Premium
of the research project specifies both the data that are needed and how they are to be obtained. The first step in the data-collection process is to look for secondary data. These are data that were developed for some purpose other than for helping to solve the problem at hand. The data that are still needed after that search is completed will have to be developed specifically for the research project and are known as primary data. The secondary data that are available are relatively quick and
Premium Marketing Research
There are many different ways to describe the data we collect and all are important when conducting business. The mean of a data set is the sum divided by the # of observations. Now saying exactly what a mean is can be helpful‚ applying it to the business world makes understanding it a lot easier. Mean can be used in a business environment by both tax offices and retailers when collecting income from a group of people; in this case both groups are interested in the total amount of money that happens
Premium Management Generally Accepted Accounting Principles Balance sheet
There are several reasons for Soton Data trained operators to move to other firms. Firstly‚ it might be due to the relationship with their employers. Employees may have unhappiness with their employers during work for example; employers are being bias towards certain employees. Secondly‚ employees have little opportunities to perform might be one of the reasons too. They are rarely showing their abilities during work or it is unchallenged to them. Soton Data might be providing employees with unattractive
Premium Employment Management Human resource management
DATA COMMUNICATION (Basics of data communication‚ OSI layers.) K.K.DHUPAR SDE (NP-II) ALTTC ALTTC/NP/KKD/Data Communication 1 Data Communications History • 1838: Samuel Morse & Alfred Veil Invent Morse Code Telegraph System • 1876: Alexander Graham Bell invented Telephone • 1910:Howard Krum developed Start/Stop Synchronisation ALTTC/NP/KKD/Data Communication 2 History of Computing • 1930: Development of ASCII Transmission Code • 1945: Allied Governments develop the First Large Computer
Premium OSI model Data transmission
Evaluation of Patient Baseline Biometric Data: Baseline data was collected at the beginning of the program‚ program completion and 3 months post program completion (Appendix A). This data included biometric data: weight‚ BMI‚ blood pressure‚ LDL and hemoglobin A1C. Blood glucose meters were downloaded and reviewed individually with patients to assist with pattern recognition and changes made to medication regimen if needed. Evaluation of Patient Generated Data: Patients were asked to rate their perceptions
Premium Statistics Blood pressure
Data & Knowledge Engineering Introduction Database Systems and Knowledgebase Systems share many common principles. Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKEreaches a world-wide audience of researchers‚ designers‚ managers and users. The major aim of the journal is to identify‚ investigate and analyze the underlying principles in the design and effective use of these systems.DKE achieves this aim
Premium Data mining Artificial intelligence
Econometric Analysis of Panel Data Badi H. Baltagi Badi H. Baltagi earned his PhD in Economics at the University of Pennsylvania in 1979. He joined the faculty at Texas A&M University in 1988‚ having served previously on the faculty at the University of Houston. He is the author of Econometric Analysis of Panel Data and Econometrics‚ and editor of A Companion to Theoretical Econometrics; Recent Developments in the Econometrics of Panel Data‚ Volumes I and II; Nonstationary Panels‚ Panel Cointegration
Premium Econometrics
(3995+L+11*Q) There are three variables in this equation‚ with the assumption; this model is realistic enough‚ if I was Sanjay‚ I will consider what the shape of the probability distribution of X is‚ and the measurement of this distribution to make risk analysis. a). Without considering the partnership opportunity‚ to solve the case‚ we run a Crystal Ball simulation with 1000 trials. The assumption variables are P‚ Q‚ and L‚ and the forecast variable is X. We found that Sanjay’s sample mean monthly salary
Premium Normal distribution Random variable Standard deviation