The RPSC Assistant Statistical Statistical Officer Syllabus 2024 has been announced for the RPSC Assistant Statistical Officer exam. There are subjects such as History and Culture, Geography and Current events and issues of Rajasthan. Apart from this, the exam will also consist of some descriptive questions. The exam will consist of objective and descriptive questions both. The objective questions will carry 150 marks and 150 questions. Each question will carry 1 mark. Read the article to know more about the topics to prepare and marking scheme.
RPSC Assistant Statistical Officer Syllabus 2024 The RPSC Assistant Statistical Officer Syllabus 2024 will comprise of a total of 3 units. These 3 units will comprise of questions from various subjects. The Unit I will consist of questions from History and Culture of Rajasthan. The Unit II will consist of questions from Geography and Natural Resources. And Unit III will consist of questions from Current events and Issues of Rajasthan.
Unit-I: History, Culture & Heritage of Rajasthan Topics Covered in History, Culture & Heritage of Rajasthan for RPSC Assistant Statistical Officer Exam Topic Description Pre & early history of Rajasthan Study of ancient and early historical periods of Rajasthan Age of Rajputs: Major dynasties of Rajasthan and the achievements of prominent rulers Overview of Rajput dynasties and their significant rulers Emergence of Modern Rajasthan Factors of socio-political awakening in the 19th century; Peasants and tribal movements of the 20th century; Political struggle and integration of Rajasthan Visual Art of Rajasthan Architecture of forts and temples; Sculpture traditions; Various schools of painting Performing Arts of Rajasthan Folk music, musical instruments, folk dance, and folk drama Various religious cults, saints, and folk deities of Rajasthan Study of religious movements, influential saints, and local deities Various dialects and its distribution in Rajasthan Examination of the dialects spoken across different regions of Rajasthan Literature of Rajasthani language Study of literary works in the Rajasthani language
Unit-II: Geography, Natural Resource & Socio-Economic Development of Rajasthan Topics Covered in Geography, Natural Resource & Socio-Economic Development of Rajasthan for RPSC Assistant Statistical Officer Exam Topic Description Geography of Rajasthan Broad physical features: Mountains, Plateaus, Plains, Desert Major rivers and lakes Study of significant rivers and lakes in Rajasthan Climate and Agro-climatic regions Examination of the climate and different agro-climatic zones Major soil types and distribution Overview of soil types and their geographic distribution Major forest types and distribution Study of forest types and their locations in Rajasthan Demographic characteristics Analysis of population characteristics and distribution Environmental issues Desertification, Droughts & Floods, Deforestation, Environmental Pollution, Ecological Concerns Economy of Rajasthan Study of major economic activities and industries Major Minerals Overview of metallic and non-metallic minerals Power Resources Renewable and Non-Renewable energy sources Major agro-based industries Industries like Textile, Sugar, Paper & Vegetable oil Poverty and Unemployment Analysis of poverty levels and unemployment rates Agro-food parks Study of agro-food parks and their significance
Unit-III: Current Events and Issues of Rajasthan and India Topics Covered in Current Events & Issues of Rajasthan and India for RPSC Assistant Statistical Officer Exam Topic Description Important Persons, Places and Current Events of the State Study of notable individuals, significant places, and current events in Rajasthan National and International events of importance Overview of significant national and international events New Schemes & Initiatives taken recently for welfare & development in Rajasthan Study of recent schemes and initiatives for welfare and development in Rajasthan
RPSC Assistant Statistical Officer Part B Syllabus The Part B will consist of descriptive questions and concerned questions from various topics. Refer to the tables below for more details.
Descriptive Statistics Syllabus Topic Description Classification, Tabulation, and Frequency Distribution Methods of organizing data into meaningful categories and presenting them in tables Diagrammatic and Graphical Representation Visual representation of data through various diagrams and graphs Bar Diagram Graphical representation of data using bars Pie Chart Circular chart divided into sectors to show proportions Histogram Graphical representation of the distribution of numerical data Frequency Polygon Line graph that represents the frequency distribution of a dataset Frequency Curve Smooth curve that represents the frequency distribution Measures of Central Tendency Statistical measures to determine the center or average of a dataset Arithmetic Mean Sum of all data points divided by the number of data points Geometric Mean The nth root of the product of n data points Harmonic Mean The reciprocal of the arithmetic mean of the reciprocals of the data points Median The middle value when the data points are arranged in ascending or descending order Mode The value that appears most frequently in a dataset Quartiles Values that divide the data into four equal parts Deciles Values that divide the data into ten equal parts Percentiles Values that divide the data into 100 equal parts Measures of Dispersion Statistical measures to describe the spread or variability of a dataset Range Difference between the maximum and minimum values in a dataset Quartile Deviation Half the difference between the first and third quartiles Mean Deviation Average of the absolute deviations from the mean Standard Deviation Square root of the variance Variance Average of the squared deviations from the mean Coefficient of Variation Standard deviation divided by the mean, expressed as a percentage Moments Quantitative measures related to the shape of the data’s distribution Measures of Skewness Measure of the asymmetry of the data’s distribution Kurtosis Measure of the “tailedness” or peakness of the data’s distribution
Probability Topic Description Classical and Axiomatic Approaches of Probability Fundamental principles and axioms of probability theory Conditional Probability Probability of an event given that another event has occurred Bayes Theorem Method to update the probability of a hypothesis based on new evidence Simple Problems on Probability Basic probability problems and exercises Random Variable and Mathematical Expectation Concepts of random variables and their expected values Chebychev’s Inequality A theorem that gives bounds on the probability that the value of a random variable deviates from its mean Probability Distributions Description of how probabilities are distributed over the values of the random variable – Probability Mass Function Function that gives the probability that a discrete random variable is exactly equal to some value – Probability Density Function Function that describes the likelihood of a random variable to take on a particular value Moment Generating Function Function used to characterize the distribution of a random variable Cumulant Generating Function Function related to the moment generating function, used to obtain cumulants Characteristic Function Another function used to describe the probability distribution of a random variable
Theoretical Distributions Topic Description Discrete Probability Distributions – Bernoulli Distribution of a random variable which has two possible outcomes – Binomial Distribution of the number of successes in a fixed number of independent Bernoulli trials – Poisson Distribution that expresses the probability of a given number of events occurring in a fixed interval – Negative Binomial Distribution of the number of trials until a specified number of successes occurs – Geometric Distribution of the number of trials until the first success – Hypergeometric Distribution of successes in draws without replacement Continuous Probability Distributions – Rectangular (Uniform) Distribution where all outcomes are equally likely – Normal Continuous distribution that is symmetric and bell-shaped – Gamma Two-parameter family of continuous distributions – Beta (Type I and Type II) Continuous distribution defined on the interval [0, 1] – Cauchy Distribution that is symmetric and has heavy tails Sampling Distributions – Chi-square Distribution of a sum of the squares of k independent standard normal random variables – t-distribution Distribution of the ratio of a normal variable to the square root of a chi-square variable divided by its degrees of freedom – F-distribution Distribution of the ratio of two scaled chi-squared distributions
Correlation, Regression, and Multivariate Analysis Topic Description Karl-Pearson’s Coefficient of Correlation Measure of linear correlation between two variables Spearman’s Rank Correlation Coefficient Non-parametric measure of rank correlation Simple Linear Regression Modeling the relationship between two variables by fitting a linear equation Method of Least Squares Mathematical procedure for finding the best-fitting curve to a given set of points Multivariate Normal Distribution Generalization of the one-dimensional normal distribution to higher dimensions Hotelling’s T² Distribution Multivariate generalization of the Student’s t-distribution Discriminant Analysis Statistical method to determine which variables discriminate between two or more naturally occurring groups Principal Component Analysis Technique for reducing the dimensionality of datasets Factor Analysis Method used to describe variability among observed variables in terms of fewer unobserved variables called factors Wishart’s Distribution Generalization of the chi-square distribution to multiple dimensions
Sampling Methods Topic Description Simple Random Sampling Sampling method where each sample has an equal probability of being chosen – With Replacement Each selected unit is returned to the population before the next unit is selected – Without Replacement Each selected unit is not returned to the population before the next unit is selected Stratified Random Sampling Dividing the population into subgroups and taking a sample from each subgroup Cluster Sampling Dividing the population into clusters and randomly selecting clusters for analysis Systematic Sampling Selecting every kth element from a population Sampling for Proportions Sampling method focused on estimating population proportions
Experimental Design Topic Description Analysis of Variance (ANOVA) Method to compare the means of three or more samples – One-way Classified Data ANOVA for one factor – Two-way Classified Data ANOVA for two factors Uniformity Trials Experiments conducted to study the uniformity of a treatment Principles of Design of Experiments Concepts such as randomization, replication, and blocking Completely Randomized Design (CRD) Experimental design where all subjects are randomly assigned to treatments Randomized Block Design (RBD) Design in which subjects are divided into blocks and then randomly assigned to treatments Latin Square Design (LSD) Design to control for two blocking factors Missing Plot Technique Method to handle missing data in experimental designs Factorial Experiments Experimental design to study the effect of two or more factors – 222^222 and 232^323 Factorial Experiments in RBD Specific designs for experiments with two or three factors – Complete and Partial Confounding Methods to deal with confounding variables in factorial experiments
Theory of Estimation and Testing of Hypothesis Topic Description Point and Interval Estimation Methods to estimate population parameters and their confidence intervals Properties of Estimators Characteristics such as unbiasedness, consistency, and efficiency Methods of Estimation Techniques such as the method of least squares and maximum likelihood estimation Confidence Interval and Confidence Limits Range of values used to estimate the true value of a population parameter Concept of Hypothesis Assumptions made about a population parameter Types of Errors Errors such as Type I (false positive) and Type II (false negative) Neyman-Pearson Lemma Fundamental lemma for hypothesis testing Parametric Tests Statistical tests that assume a specific distribution – Large Samples Tests for large sample sizes – Small Samples Tests for small sample sizes Non-parametric Tests Tests that do not assume a specific distribution – Run Test Test for randomness – Sign Test Test for median differences – Median Test Test for equality of medians
Table 8: Time Series Analysis and Index Number Topic Description Components of Time Series Analysis of trend, seasonal, cyclical, and irregular variations Measurements of Trend Methods to determine the long-term movement in time series data Seasonal Variations Regular pattern in time series data that repeats every fixed period Cyclical Variations Fluctuations in time series data over periods longer than a year Irregular Variations Random variations in time series data Autocorrelation Measure of how current values in a time series are related to past values Auto Regression Regression model where the current value depends on its previous values Periodogram Tool for identifying the periodic components in time series data Index Numbers Statistical measures to track changes in variables over time – Uses Applications of index numbers in various fields – Types Various types of index numbers, such as price, quantity, and value indices – Tests Methods to evaluate the reliability and accuracy of index numbers – Limitations Potential issues and drawbacks of using index numbers Construction of Index Numbers Methods to build index numbers – Simple and Weighted Aggregate Method Techniques to calculate index numbers using aggregate data – Simple and Weighted Average Price-relatives Methods to calculate average price changes – Chain Base Index Numbers Index numbers that use a base year that changes periodically – Base Shifting, Splicing, and Deflating Techniques to adjust and compare index numbers Cost of Living Index Numbers Index numbers that measure changes in the cost of living
Agriculture Statistics and Statistical Organization in India Topic Description Importance of Statistics in Agriculture Role of statistics in agricultural research and development Agricultural Statistical System in India Overview of the system used to collect and analyze agricultural data Agricultural Census Nationwide survey of agricultural activities Livestock
RPSC Assistant Statistical Officer Exam Pattern 2024 The RPSC Assistant Statistical Officer exam pattern will consist of a total of 150 questions. Each question will carry 1 mark. This implies that the whole paper will take place for a total of 150 marks. Refer to the table below to check the exam pattern.
Subject No. of Questions Total Marks General Knowledge of Rajasthan 40 40 Concerned Subject 110 110 Total 150 150
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