Statistical Inference Practical: Point Estimation by Method of Moment

MCQ'S based on Basic Statistics (For B. Com. II Business Statistics)

(MCQ Based on Probability, Index Number, Time Series and Statistical Quality Control Sem - IV) 1.The control chart were developed by …… A) Karl Pearson B) R.A. fisher C) W.A. Shewhart D) B. Benjamin 2.the mean = 4 and variance = 2 for binomial r.v. x then value of n is….. A) 7 B) 10 C) 8 D)9 3.the mean = 3 and variance = 2 for binomial r.v. x then value of n is….. A) 7 B) 10 C) 8 D)9 4. If sample space S={a,b,c}, P(a) = 0.6 and P(b) = 0.3 then P(c)=….. A)0.6 B)0.3 C)0.5 D)0.1 5 Index number is called A) geometer B)barometer C)thermometer D)centimetre 6. Index number for the base period is always takes as

Basic Concepts of Probability and Binomial Distribution

Probability: Basic concepts of Probability: Probability is a way to measure hoe likely something is to happen. Probability is number between 0 and 1, where probability is 0 means is not happen at all and probability is 1 means it will be definitely happen, e.g. if we tossed coin there is a 50% chance to get head and 50% chance to get tail, it can be represented in probability as 0.5 for each outcome to get head and tail. Probability is used to help us taking decision and predicting the likelihood of the event in many areas, that are science, finance and Statistics. Now we learn the some basic concepts that used in Probability: i) Random Experiment OR Trail: A Random Experiment is an process that get one or more possible outcomes. examples of random experiment include tossing a coin, rolling a die, drawing a card from pack of card etc. using this we specify the possible outcomes known as sample pace. ii)Outcome: An outcome is a result of experiment. an outcome is one of the pos

Statistical Inference II Notes

Likelihood Ratio Test

Measures of Central Tendency :Mean, Median and Mode

Changing Color Blog Name Measures of Central Tendency I. Introduction. II. Requirements of good measures. III. Mean Definition. IV . Properties V. Merits and Demerits. VI. Examples VII. Weighted Arithmetic Mean VIII. Median IX. Quartiles I. Introduction Everybody is familiar with the word Average. and everybody are used the word average in daily life as, average marks, average of bike, average speed etc. In real life the average is used to represent the whole data, or it is a single figure is represent the whole data. the average value is lies around the centre of the data. consider the example if we are interested to measure the height of the all student and remember the heights of all student, in that case there are 2700 students then it is not possible to remember the all 2700 students height so we find out the one value that represent the height of the all 2700 students in college. therefore the single value represent the whole data and

Time Series

Time series Introduction:- We see the many variables are changes over period of time that are population (I.e. population are changes over time means population increase day by day), monthly demand of commodity, food production, agriculture production increases and that can be observed over period of times known as time series. Time series is defined as a set of observation arranged according to time is called time series. Or a time Series is a set of statistical observation arnging chronological order. ( Chronological order means it is arrangements of variable according to time) and it gives information about variable. Also we draw the graph of time series to see the behaviour of variable over time. It can be used of forecasting. The analysis of time series is helpful to economist, business men, also for scientist etc. Because it used to forecasting the future, observing the past behaviour of that variable or items. Also planning for future, here time series use past data h

Classification, Tabulation, Frequency Distribution, Diagrams & Graphical Presentation.

Business Statistics I Classification, Tabulation, Frequency Distribution , Diagrams & Graphical Presentation. In this section we study the following point : i. Classification and it types. ii. Tabulation. iii. Frequency and Frequency Distribution. iv. Some important concepts. v. Diagrams & Graphical Presentation I. Classification and it's types: Classification:- The process of arranging data into different classes or groups according to their common characteristics is called classification. e.g. we dividing students into age, gender and religion. It is a classification of students into age, gender and religion. Or Classification is a method used to categorize data into different groups based on the values of specific variable. The purpose of classification is to condenses the data, simplifies complexities, it useful to comparison and helps to analysis. The following are some criteria to classify the data into groups. i. Quantitative Classification :-

Sequential Analysis: (SPRT)

Sequential Analysis: We seen that in NP theory of testing hypothesis or in the parametric test n is the sample size and is regarded as fixed and the value of α fixed , we minimize the value of β. But in the sequential analysis theory invented by A Wald in sequential analysis n is the sample number is not fixed but the both values α and β are fixed as constant. Sequential Probability Ratio Test: (SPRT):

Measures of Dispersion : Range , Quartile Deviation, Standard Deviation and Variance.

Measures of Dispersion : I. Introduction. II. Requirements of good measures. III. Uses of Measures of Dispersion. IV. Methods Of Studying Dispersion: i. Absolute Measures of Dispersions : i. Range (R) ii. Quartile Deviation (Q.D.) iii. Mean Deviation (M.D.) iv. Standard Deviation (S. D.) v. Variance ii. Relative Measures of Dispersions : i. Coefficient of Range ii. Coefficient of Quartile Deviation (Q.D.) iii. Coefficient of Mean Deviation (M.D.) iv. Coefficient of Standard Deviation (S. D.) v. Coefficient of Variation (C.V.) I. Introduction. We have the various measures of central tendency, like Mean, Median & Mode, it is a single figure that represent the whole data. Now we are interested to study this figure(i.e. measures of central tendency) is proper represe

Business Statistics Notes ( Meaning, Scope, Limitations of statistics and sampling Methods)

Business Statistics Paper I Notes. Welcome to our comprehensive collection of notes for the Business Statistics! my aim is to provided you with the knowledge you need as you begin your journey to comprehend the essential ideas of this subject. Statistics is a science of collecting, Presenting, analyzing, interpreting data to make informed business decisions. It forms the backbone of modern-day business practices, guiding organizations in optimizing processes, identifying trends, and predicting outcomes. I will explore several important topics through these notes, such as: 1. Introduction to Statistics. : meaning definition and scope of Statistics. 2. Data collection methods. 3. Sampling techniques. 4. Measures of central tendency : Mean, Median, Mode. 5. Measures of Dispersion : Relative and Absolute Measures of dispersion, Range, Q.D., Standard deviation, Variance. coefficient of variation. 6.Analysis of bivariate data: Correlation, Regression. These notes will serve as you

Statistical Quality Control

Statistical Quality Control Statistical quality control (S. Q. C.) is a branch of Statistics it deals with the application of statistical methods to control and improve that quality of product. In this use statistical methods of sampling and test of significance to monitoring and controlling than quality of product during the production process. The most important word in statistical Quality control is quality The quality of product is the most important property while purchasing that product the product fulfill or meets the requirements and required specification we say it have good quality or quality product other wise not quality. Quality Control is the powerful technique to diagnosis the lack of quality in material, process of production. Causes of variation: When the product are produced in large scale there are variation in the size or composition the variation is inherent and inevitable in the quality of product these variation are classified into two causes. 1) chan

Shree GaneshA Statistics

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