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Data analysis provides a means for evaluation of collected observations and information. Data analysis is simply the act of transforming data into useful information and facilitating conclusions. |
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Using Data analysis techniques such as narratives, charts, graphs and tables are used to describe, summarize, and compare the collected data. |
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Probability is the branch of mathematics that measures the likelihood that an event will happen. The word Probability comes from the Latin word probare (to prove, or to test). |
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Probability is expressed as a number between 0 and 1. The probability of an impossible event is 0, and that of an event that is certain to occur is 1. |
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Statistics |
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Statistics is about collection of information and its presentation and about drawing inferences from these. We come across facts and figures in the newspapers, Television and the radio. The numerical figures are called "the data". If we have to draw good inferences from information collected, it has to be presented properly. We shall now study how the data collected is tabulated. |
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The collection of data, its classification, tabulation and study is called Statistics. |
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Quantities such as height, weight, age, amount can have several different values. Quantities which can assume different numerical values are called variables. Variables are of two types: (a) Continuous (b) Discrete. |
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Graphical Representation |
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The graphical representation of data makes the reading more interesting, less time-consuming and easily understandable. The disadvantage of graphical presentation is that it lacks details and is less accurate. In our study, we have the following graphs: 1. Bar Graphs 2. Pie Charts 3. Frequency Polygon 4. Histogram. |
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Statistics: Graphical Representation |
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The scientific methods of collection of data, its classification and application to commerce and everyday life is called statistics. A list of some important terms as follows: (i) ungrouped data (ii) tabulation of data (iii) range (iv) frequency (v) frequency distribution (vi) tally (vii) inclusive type of grouped frequency distribution (viii) exclusive type of grouped frequency distribution (ix) lower limit and actual lower limit (x) upper limit and actual upper limit (xi) class size or class width (xii) class mark or class mid-interval (xiii) Variables (xiv) Continuous Variables (xv) Discrete Variables. |
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Statistics XI |
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Today graphics, tables, reasoning, estimation and prediction are playing a very important role in stating the facts in terms of figures. |
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Statistics deals mainly in communicating facts and figures in terms of a method called statistical method. Collection, classification, tabulation, representation, reasoning, testing and drawing inferences are part of statistical methods. |
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The word statistics is used with two meanings.
1. Systematically collected and presented numerical data.
2. Processing the numerical data and to draw conclusions from there. |
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Measures of Central Tendency |
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When some data is colleted, we have certain numbers which represent the characteristics of the data, around which the data appears to be concentrated, we call such numbers as the measures of central tendency. There are three measures of central tendency. (i) Mean (ii) Median and (iii) Mode. |
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Permutations and Combinations |
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The different arrangements that can be made with a given number of things taking some or all of them at a time are called permutations. |
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The selection of a number of things taking some or all of them at a time are called combinations. |
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Probability - I |
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An experiment repeated under essentially homogeneous and similar conditions results in an outcome, which is unique or not unique but may be one of the several possible outcomes. When the result is unique then the experiment is called a deterministic experiment. |
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Any experiment whose outcome cannot be predicted in advance, but is one of the set of possible outcomes, is called a random experiment. |
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If we think an experiment as being performed repeatedly, each repetition is called a trial. We observe an outcome for each trial. |
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The set of all possible outcomes of a random experiment is called the sample space, associated with the random experiment. |
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Probability (continued) |
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Let A and B be any two events associated with a random experiment. The probability of occurrence of event A when the event B has already occurred is called the conditional probability of A when B is given and is denoted as P(A/B). |
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Linear Programming |
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The mathematical models which tells to optimise (minimize or maximise) the objective function Z subject to certain condition on the variables is called a Linear programming problem (LPP).
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Questions and Answers 1 |
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Questions and Answers 2 |
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