STAGE 1

PROBABILITY AND STASTICS stage 1.

MIND MAP STAGE 1 PROBABILITY AND STASTICS.

RECOVERY WHAT IS STASTICS? DATA ORGANIZATION UNDERSTANDING ANALYSIS GRAPHIC REPRESENTATION AND THEIR INTER FREQUENCY AND FREQUENCY DISTRIBUTION SELF- EVALUATION LEARNING EVIDENCE INDEX.

WHAT IS STASTICS?.

STATICS DESCRIPTIVE INFERENCIAL.

WHAT IS STASTICS? COLLECTING ORGANIZING SUMMARIZING ANALYZING INTERPRETING DATA CONCLUSION.

TYPES OF STATICS Descriptive stastics: 1.Is the responsable for the collection,organization, presentation and analysis of data from population..

2.No conclusion or inference is made about a larger group,only for the analyzed group. TYPES OF STATICS NO CONCLUSION.

TYPES OF STATICS 3.The collected data is summarized in a appropiate tables and graphs that clearly show the information..

Inference stastics:Is responsable to conclusions from descriptive stastics. TYPES OF STATICS.

POPULATION:it is the set of all the individuals(people,animals or things) on which the study will be carried out,that is,the set in which some characteristic that can be identified and measured will be observed. BASIC CONCEPTS.

FINITE POPULATION:Is the one in which it is possible to enumerate the elements of said population,since the size is known. BASIC CONCEPTS.

INFINITE POPULATION:is where the number of elements in the population is not known,therefore cannot be counted BASIC CONCEPTS.

STASTITICAL POPULATION:It ias the set of all the data obtained when measuring a variable in the elements of the population BASIC CONCEPTS.

SAMPLE:It is a representative subset of the population from which inferences are made regarding that population to which it belongs. BASIC CONCEPTS.

SAMPLE: BASIC CONCEPTS PROBABILISTIC:It is a sample which each element of the population,has the same probability of being selected to be part of it..

SAMPLE: BASIC CONCEPTS NON-PROBABILISTIC:it is a sample that is not obtained by a random selection process,but throught the accesibility,criteria or judgment of the person who selects the elements of the sample.

INDIVIDUAL O STATISTICAL UNIT:It refers to each of the elements that belong to the population,hich can be measured or qualified. BASIC CONCEPTS.

1.VARIABLE:It is a characteristic of the population or of the sample whose measurement can change its value,it is represented by letters of the alphabet BASIC CONCEPTS 2.Depending on its nature,it can be measured or qualified ..

QUALITATIVE VARIABLE:It is the variable that represents non-numeric qualities,attributes,or characteristics,for example:marita status,hair color,profession (ordinal and nominal) BASIC CONCEPTS.

BASIC CONCEPTS QUANTITAVE VARIABLE:It is the variable that is represented numerically,for example;weight,height,age. The quantitative vaariable can be continous and discrete..

CONTINUOS VARIABLE:It is the variable whose values are represneted by the set of real,that is,it can take any real value within an interval,for example,the height of a group of teeenagers. BASIC CONCEPTS.

Discrete variable:It is the variable whose values are represented by the set of natural numbers,for example,the number of siblings of each student in a group BASIC CONCEPTS.

Dichotomous variable:It is a quantitative and qualitative variable that can only take two values such as yes-no,male -female BASIC CONCEPTS yes no.

DATUM:It is the value obtained for each individual to the population or study sample according to the variable that is established for the emausrement,(plural:data) BASIC CONCEPTS.

NOMINAL SCALE: On this scale,the data are labels to identify and classify,there is no order of preference between them,as a example,we have profession,registration,brand MEASUREMENT SCALES QUALITATIVE Boss Excute common worker.

QUALITATIVE ORDINAL SCALE:The data indicates a relative position,so there is an order between them,either from smallest to largest or viceversa.For example,the classification of soccer teams or the levels of satisfaction for a service. MEASUREMENT SCALES PORTERO DELANTERO JUAGADOR.

Interval scale:The data represent magnitudes and the distance between the scale values is equal. Measurement scales Quantitative: INTERVAL=DISCRETE.

Measurement scales Quantitative: In this scale we can perform addition and substraction operations,but not division and multiplication. It is addition and substraction because you say that 20 -10=10.

This scale does not have and absolue zero,since this value does not refer to te absence of the measured characteristic,but rather it is avlue that is placed somewhere on the scale. Measurement scales Quantitative:.

An example of this scale is the temperature measured in Celsius,since the distance between two values can bedetrmined,for example,the distance between 20°C and 25°C is the same as between 40°C and 45°C,but you can’t say that 20°C is half the temperature of 40°C,furthermore,0°C does not indicate the absence of temperature.Other examples are the measurement of the IQ or the alttitude of certain cities in relation to sea level,among others. Measurement scales Quantitative:.

Measurement scales Ratio scale:On this scale,zero is value that indicates the absence of the measured characteristic. RATIO=CONTINUOS.

Addition,susbtraction,multiplication,and division operations can be performed on their values and have meaning,that is,by comparing two values,it is possible to determine the distance between them, as well as how many times one value is greater tha another ,some examples of this scale are weight,height,age or anything that can be used as a reference to the numbers on a number line. Measurement scales ADDITION SUBSTRACTION MULTIPLICATION DIVISION.

Data sources: are the locations from which information comes. DATA SOURCES Data can be obtained from existing sources (Documentary research) or through surveys and experimental studies..

DOCUMENTARY RESEARCH:It consists of obtaining data by consulting avalable sources of information. DATA SOURCES BOOKS MAGAZINES ELECTRONIC RESOURCES DOCUMENTARIES FILES.

DATA SOURCES SURVEY:It is the most used instrument to collect data and consits of set of questions regarding one or more variables to be measured within a populatio under study..

DATA SOURCES Experiment:It is a planned and controlled procedure that is used in scientific research to obtain information that allows to know the behavior of some process. For example determining the effects of a medication to control a disease,or the change in the academic achievement of students in the face of different types of learning.

DATA ORGANIZATION DATA ORGANIZATION:It is necessary to organize them to quickly visualize the characteristics of what was collected and facilitate its analysis.

1.DESCENDING- ASCENDING(VICEVERSA) 2.STEM AND LEAF PLOT 3.DOUBLE STEM LEAF PLOT DATA ORGANIZATION.

EXAMPLE 1 ASCENDING TO DESCENDING ORDER EXAMPLE 1:A study was carried out on the height(in centimeters) of 30 students of a first semester group .The results were the following:.

EXAMPLE 1 168 165 168 171 170 159 182 177 168 158 170 158 170 158 168 172 159 163 166 165 172 158 167 178 165 175 ALTOS 170-180 MEDIANOS160-169 CHICOS 159 PARA ABAJO Individual Repetidos A A C LETRAS CON COLOR DE CIRCULO A C B D F E E B A D E D E C B E A A A A B B G.

ACOMODA 182,179,178,175,172,172,171,170,170, 168,168,168,168,167,166,165,165,165, 163,159,159,159,158,158,158 ASCENDENTE A DESCENDENTE.

STEM AND LEAF PLOT Example 2:The table shows the results of a physics exam for a group of 35 students sort th data using a stem and leaf plot.

STEM AND LEAF PLOT This is a metod to order quantitative data in which a”Stem” is created with the digits that represents the largest place values in the data set,the “leaves” 6 4 1 2 3 7 8 5 9.

STEM AND LEAF PLOT 6 4 1 2 3 7 8 5 9 0 1 2.

DOUBLE STEM PLOT TWO GROUPS 15 16 17 18 6 4 1 2 3 7 8 5 9 0 1 2.

Example 5:In an ice cream shop,40 people were asked what flavor of ice cream they preffered and the results were recorded in the table.How would be qualitative data be ordered? SORTING QUALITATIVE DATA The data of different values is written down in the first column,and,in the second column,the number of times that value appears in the study is recorded using a vertical line.

1-DAZAI 2-CHUUYA 3.KUNIKIDA 4.ATSUKI 5-KENJI SORTING QUALITATIVE DATA.

A distribution or frequency table is the joint representation of the data in the form of a table subgroup correponding to a study situation and is organized according to the number of observations,that correspond to each or each data group. Frequency distribution for ungrouped data.

The elements that make up a statistical table and table title,heading and content or body 1.Absolute frequency: (f).It is the number of time data appears (F).