Biostatics

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Biostatics

  1. 1. 1 Biostatistics
  2. 2. 2 MEANINGS OF STATISTICS  Numerical Facts Systematically Arranged.  Subject. Statistics is the mathematical science of making decisions and drawing conclusions from data in situations of uncertainty. It includes collection, organization and analysis of numerical data. Statistics of prices, Statistics of road accidents, Statistics of crimes, Statistics of birth, Statistics of deaths, Statistics of educational institutions etc. 
  3. 3. 3 INTRODUCTORY STATISTICS OR Statistics is a science, pure and applied, of creating, developing and applying techniques such that uncertainty of inductive inferences may be evaluated. Statistic. A numerical quantity calculated from a sample.
  4. 4. Biostatistics When the data analyzed are derived from the biological sciences and medicine, we use the term biostatistics to distinguish this particular application of statistical tools and concepts
  5. 5. Types of Statistics Descriptive Statistics: Methods of organizing, summarizing, and presenting data in an informative way. Inferential Statistics: A decision, estimate, prediction, or generalization about a population, based on a sample
  6. 6. 6 Population:- The collection of all possible observations whether finite or infinite, relevant to some characteristic of interest is called a population. The number of observations in a finite population is called size of the population and is denoted by N. INTRODUCTORY STATISTICS Sample: A sample is a part of a population. Generally it consists of some of the observation. The number of observations in a sample is called size of the sample and is denoted by n.
  7. 7. 7 INTRODUCTORY STATISTICS Observation: The numerically recording of information is called observation/datum. Data: The set of observations is called data. Example: It was observed that out of 500 rabbits caught, 300 were females. Is there evidence that more rabbits in this country are females?
  8. 8. 8 INTRODUCTORY STATISTICS Parameter: It is a quantity computed from a population if the entire population is available. Parameters are fixed or constant quantities and not usually known.
  9. 9. 9 INTRODUCTORY STATISTICS Variable: A characteristics that varies from individual to individual is called a variable. For example age, plant height, weight, no of plants per plot etc are variables as they vary from individual to individual. Constant: Quantity which do not vary from individual to Individual is called constant. e.g. e= 2.71828 , = 3.145
  10. 10. 10 Basic concepts Descriptive Statistics Presenting the numerical information in the form of number, graphs and tables. Inferential Statistics To estimate the population parameter on the basis of the sample statistic. Population The aggregate of units under discussion. Sample A subset / part of the population.
  11. 11. 11 INTRODUCTORY STATISTICS Types of variables: Fixed or Mathematical Variable: A variable may be fixed or Mathematical when its value can be determined before hand. e.g. amount of fertilizer to be applied to a plot, amount of insecticide applied to control insect pests. Random Variable: A variable may be random when its value cannot be exactly determined. e.g. yield from a plot
  12. 12. 12 INTRODUCTORY STATISTICS Types of variables: (1):- Quantitative variable (2):- Qualitative variable. Quantitative variable:- A variable is called Quantitative variable when a characteristic can be expressed numerically such as weight, income, number of children. Qualitative variable:- If a characteristic is non-numerical such as sex, colour, general knowledge, honesty, beauty, etc the variable is called Qualitative/ Categorical variable or attribute.
  13. 13. 13 INTRODUCTORY STATISTICS Types of Quantitative variable 1:- Discrete variable 2:- Continuous variable . Discrete variable:- A variable which can assume some specific values within a given range is called a discontinuous or discrete variable. e.g. number of trees in a field, number of leaves in a tree. A discrete variable takes on values which are integers or whole numbers. Continuous variable:- A variable which can assume any value (fractional or integral) within a given range is called a continuous variable. For example Height of a plant, the temperature at a place.
  14. 14. 14 Variable Characteristic that varies form individual to individual a) Fixed variable b) Random variable Types of Variable Quantitative variable Capable of assuming a numerical value Continuous variable Can take all possible values in an interval Discrete/Discontinuous variable Can take only specified values Qualitative/Categorical variable Not capable of taking numerical measurements • Constant Don’t vary from individual to individual
  15. 15. 15 INTRODUCTORY STATISTICS Scales of Measurement Measurement: Measurement refer to “Assigning of number to observations or objects. Scaling: Scaling is a process of measuring. Four Scales of Measurements 1. Nominal Scale 2. Ordinal Scale 3. Interval Scale 4. Ratio Scale Four Scales of Measurements
  16. 16. 16 INTRODUCTORY STATISTICS Nominal Scale (Weakest form of measurement) Nominal: Classifies variables simply in terms of their names and the categories cannot be ranked. The variable “religion” with the response categories “Christian,” “Jewish,” “Muslim,” etc. is an example of a nominal scale of measurement. Rainfall may be classified as • Heavy • Moderate • Light
  17. 17. 17 INTRODUCTORY STATISTICS Ordinal Scale (When numbers are allocated in some order) It includes the characteristics of nominal scale and in addition has a property of ordering or ranking of measurements. • Attitude scale Strongly agree, agree, disagree • Social scale Upper, middle, lower • Performance of players Excellent, good, fair, poor
  18. 18. 18 INTRODUCTORY STATISTICS Interval Scale Interval: Contains categories in which the actual distances, or intervals, between categories can be compared. For example, we can say that the difference between ages 20 and 25 is the same as the difference between ages 50 and 55. Ratio Scale Variables at a ratio scale of measurement are, typically, those such as age, number of children, etc. The values of these variables have a real "zero" value. • Height of plant, weight of students, volume, length,

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