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 Slide 1 : LITTLE FLOWER HOUSE KAKaRMATTA MATHS PRESENTATION LOADING . . .
 Slide 2 : INTRODUCTION A very good morning to all. Today we the student of class IX are here to give presentation on statistics. Statistics is a vast subject but we have tried to give a glimpse on the basis of data we have included in our presentation some : * Basic concept of statistics * Measures of central tendency
 Slide 3 : What is statistic ? * A branch of mathematics that provide techniques to analyze whether or not your data is significant .( meaningful) * Statistical application are based on probability statement. * Nothing is “proved” with statistic. * Statistic report the probability that similar result would occur if you repeated the experiment.
 Slide 4 : Statistical data In statistic there are two types of data: Primary data: when an investigator collects data himself with a definite plan or design in his mind, it is called primary data. Secondary data: data which are not originally collected rather obtained from published or unpublished source are known as secondary data. For the processing of the data we have to arrange in order instance is very important.
 Slide 5 : Presentation of data The raw data can be arranged in three ways: Serial order or alphabetical order. Ascending order. Descending order. Frequency Observation occurring number of times in a given data is called frequency.
 Slide 6 : Frequency distribution It is of two types: Discrete frequency distribution (tally marks) Continuous or grouped frequency distribution (class interval, class width, class limit)
 Slide 7 : Class interval:-To present a large amount of data so that a reader can make sense of it easily we condense it into groups. These groups are called “Classes” or “Class Intervals”. CLASS LIMIT:- The variant values of the classes or groups are called the class limits. The smaller value of the class is called lower class limit and larger value of the class is called upper class limit. Class limits are also called inclusive classes. For Example:- Let us take the class 10 – 19, the smaller value 10 is lower class limit and larger value 19 is called upper class limit. Class width:- It is the difference between the two boundaries of a class.
 Slide 8 : Graphical representation of statistical data What is graphical representation? One of the most appealing way and convincing ways to of presenting the data is through pictures and graphs, because graphs or pictures, if drawn attractively , are eye catching and make unwieldly data easily intelligible. Moreover graphs are good visual aids. There are various method of graphical representation of frequency distribution.
 Slide 9 : What are the various types? Bar graphs Histogram Frequency polygon Bar graph: A bar graph is pictorial representation of the numerical data by a number of bars(rectangle) of uniform width erected horizontally or vertical with equal spacing between them.
 Slide 10 : While constructing bar graphs the following points should be kept in mind: The width of the bars should be uniform throughout. The gap between one bar and another should be uniform throughout. Bars may be either horizontal or vertical. The vertical bars should be preferred because they give a better look.
 Slide 11 : Example: The following table shows enrollment of students in introductory subjects. Represent the above information by a bar graph.
 Slide 12 : 2. Histogram : A histogram or a frequency histogram is a graphical representation of a frequency distribution in the form of rectangles with class interval as bases and heights proportional to corresponding frequencies such that there is no gap between any two successive rectangle. While constructing histogram the following points should be kept in mind: A continuous grouped frequency distribution with equal intervals. A continuous grouped frequency distribution with unequal interval.
 Slide 13 : iii)A frequency distribution in which mid-point of class-intervals are given. iv)A grouped frequency distribution in which class intervals are given in inclusive form. Example: the following table shows the height of Black Cherry trees(in feet). Represent this data in the form a histogram.
 Slide 14 : 3. Frequency polygon Example: the following table shows the weight of the students of class IX. Represent the above data by frequency polygon Frequency polygon is a closed figure got by joining the middle points of the top of rectangle of histograms, extremes are joined with x-axis at a distance of half the length of class- interval from the extremes of the variable of the class interval.
 Slide 15 : Measures of central tendency What is measures of central tendency ? In the case of quantitative variables or those of qualitative variables which can be measured quantitatively the information contained in the raw data, or in the associated frequency table can also be presented by means of few numerical values. Methods providing such values are called ‘Measures of Location or Measures of Central Tendency’.
 Slide 16 : What are the various types? Mean Median Mode 1. Mean : If you are using a sample population Arithmetic Mean (average) The mean shows that ½ the members of the pop fall on either side of an estimated value
 Slide 17 : 2. Median: The middle number. * If you have an odd number of data then the median is the value in the middle of the set. * If you have an even number of data then the median is the average between the two middle values in the set. 3. Mode: Most frequently seen value (if no numbers repeat then the mode = 0)
 Slide 18 : CONCLUSION So, in the end we would like to say that we hope we have been able to give an idea about the basics of “Statistics”.
 Slide 19 : THAnK YOU