Mans ciemats rudenī
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презентация реки и озёра
Сергеева Ольга Ивановна,
Лукановская Марина Тафкиловна
учителя начальных классов КГУ "СОШ №54"
день дошкольного работника
27 сентября 2016 года в актовом зале Центральной школы прошли торжественные мероприятия, посвященные профессиональному празднику - Дню дошкольного работника.
Recommended
презентация реки и озёра
Сергеева Ольга Ивановна,
Лукановская Марина Тафкиловна
учителя начальных классов КГУ "СОШ №54"
день дошкольного работника
27 сентября 2016 года в актовом зале Центральной школы прошли торжественные мероприятия, посвященные профессиональному празднику - Дню дошкольного работника.
Vendija
A 14-year-old girl named Vendija describes her interests which include drawing, painting, fashion and spending time with her perfect friends and family. She enjoys activities common among Latvian girls like riding bikes, various sports, music and winter activities. Her school has nice teachers and students where she recently had a fun art project painting landscapes.
Exploring data histograms
Histograms are used to graphically represent the distribution of data by dividing it into intervals and counting the frequency of data points within each interval. To construct a histogram, the data is divided into bins of equal width and a frequency table is made listing the count in each bin. The bins are then graphed on the x-axis with their corresponding frequencies on the y-axis. Patterns in histograms can reveal the center, shape, spread and skewness of the distribution through characteristics like peaks, symmetry, outliers and the range of values.
Stat 4 the normal distribution & steps of testing hypothesis
The document discusses the normal distribution and statistical hypothesis testing. It notes that the normal distribution is also called the Gaussian distribution, and has equal mean, median and mode. It then discusses how much of the data falls within standard deviations of the mean for the normal distribution. The document also covers confidence intervals for means, the steps of statistical hypothesis testing including assumptions, hypotheses, significance levels and tests, and different statistical tests used for numerical and categorical data like t-tests, ANOVA, regression and correlation.
Chapter 3: Prsentation of Data
This document discusses different methods for presenting data, including textual, tabular, and graphical presentations. Tabular presentations include frequency distribution tables that are ungrouped, grouped, simple, and complete. Graphical presentations include bar charts, histograms, frequency polygons, pie charts, and pictographs to visually depict quantitative data using bars, rectangles, lines, circles, or pictures. The examples provided demonstrate how to construct different types of tables and graphs for a set of sample data.
Normal Distribution
This document discusses the normal distribution and related concepts. It begins with an introduction to the normal distribution and its properties. It then covers the probability density function and cumulative distribution function of the normal distribution. The rest of the document discusses key properties like the 68-95-99.7 rule, using the standard normal distribution, and how to determine if a data set follows a normal distribution including using a normal probability plot. Examples are provided throughout to illustrate the concepts.
Measures of Dispersion
If everything were the same, we would have no need of statistics. But, people's heights, ages, etc., do vary. We often need to measure the extent to which scores in a dataset differ from each other. Such a measure is called the dispersion of a distribution.
Graphical Representation of Data
Professor Sana Rehman, Assistant Professor, SCMS Pune talks all about GRAPHICAL REPRESENTATION OF DATA.
Contents:
1. Terminology
2. Qualitative and Quantitative Data
3. Continuous and Discrete Data
4. Primary and Secondary Data
5. Meaning of Statistics
6. Importance of the Organization of India
7. Arranging data in a sequence
8. Grouping and Tabulation of Data
9. Tally table
10. Histogram
11. Bar diagram or bar graph
12. Frequency Polygon
13. Cumulative Frequency Curve or Ogive
14.
Demography
Demography is the statistical study of human populations and encompasses the size, structure, and distribution of populations over time and space in response to births, deaths, and migration. Demographic data can be collected directly from vital records like censuses or birth/death records, or indirectly by surveying samples about topics like fertility rates. The scope of demography includes both macro-level trends like economic issues and population growth, as well as micro-level topics like individual families. A balanced view of demography encompasses factors like population size, composition, distribution, labor forces, and population policies.
Statistics-Measures of dispersions
This document discusses various measures of dispersion in statistics including range, mean deviation, variance, and standard deviation. It provides definitions and formulas for calculating each measure along with examples using both ungrouped and grouped frequency distribution data. Box-and-whisker plots are also introduced as a graphical method to display the five number summary of a data set including minimum, quartiles, and maximum values.
Measures of central tendency
- There are three main measures of central tendency: the mean, median, and mode. The mean is the average and is calculated by adding all values and dividing by the total number. The median is the middle value when data is arranged in order. The mode is the most frequently occurring value.
- To determine which measure to use, consider if the data has extreme values and whether the most common value is needed over the average. The mean can be skewed by outliers while the median and mode are more robust. The appropriate measure depends on the characteristics of the specific data set.
Normal distribution stat
1) The document discusses the characteristics and properties of the normal distribution, including that it is bell-shaped and symmetrical about the mean.
2) It defines z-values as a way to standardize normal distributions by transforming data values into standard scores based on the mean and standard deviation.
3) Examples are provided to demonstrate calculating probabilities using the standard normal distribution, such as finding the percentage of observations that fall within a certain number of standard deviations from the mean.
Normal Probability Distribution
The document discusses properties of normal distributions and the standard normal distribution. It provides examples of finding probabilities and values associated with normal distributions. The key points are:
- Normal distributions are continuous and bell-shaped. The mean, median and mode are equal.
- The standard normal distribution has a mean of 0 and standard deviation of 1.
- Probabilities under the normal curve can be found using z-scores and the standard normal table.
- Values like z-scores can be determined by finding the corresponding cumulative area in the standard normal table.
Measure of dispersion part I (Range, Quartile Deviation, Interquartile devi...
This tutorial gives the detailed explanation of "Measure of Dispersion" (Range, Quartile Deviation, Interquartile Range, Mean Deviation) with suitable illustrative example with MS Excel Commands of calculation in excel.
Population and demography
Population and demography are major areas of study for social scientists. A population is defined as a group of individuals occupying a particular place at a given time. Key factors in defining a population are group, place, and time. Population growth impacts issues like housing, food security, and the environment. Demography statistically analyzes population characteristics like size, composition by age and sex, birth and death rates, and immigration. Demographic data is important for policymaking and predicting future trends. Sources of demographic data include censuses, vital statistics like birth and death records, and surveys. Population change is influenced by fertility, mortality, and migration. Population pyramids display the age and sex structure of a population.
STATISTICS: Normal Distribution
The document provides an outline and explanation of key concepts related to the normal distribution. It begins with an introduction to probability distributions for continuous random variables and the definition of a density curve. It then defines terms and symbols used in the normal distribution, including mean, standard deviation, and z-scores. The document explains the characteristics of the normal distribution graphically and provides examples of finding areas under the normal curve using z-tables. It concludes with examples of finding unknown z-values and calculating probabilities for specific scenarios involving the normal distribution.
Vital statistics
The document discusses vital statistics, which are numerical records of life events like births, deaths, marriages, and divorces that can be used to study public health trends. Vital statistics are collected through civil registration systems and sample surveys. They provide data to evaluate health programs, plan for disease control, inform legislation and policymaking, and allow comparisons between populations. Important vital statistics include crude death rate, age-specific death rate, infant mortality rate, neonatal mortality rate, post-neonatal mortality rate, and maternal mortality rate.
Demography
Demography is the study of human populations focusing on population size, composition, and distribution. It deals with 5 demographic processes: fertility, mortality, marriage, migration, and social mobility. Demography can be static, focusing on population structure, or dynamic, focusing on changing patterns of mortality, fertility, and migration. India's population growth rate is the net of crude birth and death rates. India's population is young with 34.33% under 15 and growing elderly population above 60 years. Sex ratio is females per 1000 males and is adverse to women in India. Dependency ratio considers under 15 and over 65 as dependent on 15-64 age group. India's age pyramid is broad at the base and tapering at the top.
Normal distribution and sampling distribution
This document provides an overview of Chapter 5 from the textbook, which covers normal probability distributions. Section 5.1 introduces normal distributions and the standard normal distribution, including their key properties and how to interpret related graphs. It describes how any normal distribution can be transformed into a standard normal distribution for calculation purposes. Section 5.1 also shows how to find areas under the standard normal curve using the standard normal table. Section 5.2 discusses how to calculate probabilities for normally distributed variables by relating them to areas under the normal curve. It provides examples of finding probabilities and expected values.
Vital statistics and demography
This document provides an overview of vital statistics and demography. It defines vital statistics as data dealing with human mortality, morbidity and demography. Key sources of population data are identified as censuses, registration of vital events, sample registration surveys, and institutional records. Details are given on census taking methods, uses of censuses, census in Nepal, information collected in censuses, and measurement of population, mortality, fertility, and other demographic indicators.
Graphical presentation of data
Variables describe attributes that can vary between entities. They can be qualitative (categorical) or quantitative (numeric). Common types of variables include continuous, discrete, ordinal, and nominal variables. Data can be presented graphically through bar charts, pie charts, histograms, box plots, and scatter plots to better understand patterns and trends. Key measures used to summarize data include measures of central tendency (mean, median, mode) and measures of variability (range, standard deviation, interquartile range).
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A 14-year-old girl named Vendija describes her interests which include drawing, painting, fashion and spending time with her perfect friends and family. She enjoys activities common among Latvian girls like riding bikes, various sports, music and winter activities. Her school has nice teachers and students where she recently had a fun art project painting landscapes.
Exploring data histograms
Histograms are used to graphically represent the distribution of data by dividing it into intervals and counting the frequency of data points within each interval. To construct a histogram, the data is divided into bins of equal width and a frequency table is made listing the count in each bin. The bins are then graphed on the x-axis with their corresponding frequencies on the y-axis. Patterns in histograms can reveal the center, shape, spread and skewness of the distribution through characteristics like peaks, symmetry, outliers and the range of values.
Stat 4 the normal distribution & steps of testing hypothesis
The document discusses the normal distribution and statistical hypothesis testing. It notes that the normal distribution is also called the Gaussian distribution, and has equal mean, median and mode. It then discusses how much of the data falls within standard deviations of the mean for the normal distribution. The document also covers confidence intervals for means, the steps of statistical hypothesis testing including assumptions, hypotheses, significance levels and tests, and different statistical tests used for numerical and categorical data like t-tests, ANOVA, regression and correlation.
Chapter 3: Prsentation of Data
This document discusses different methods for presenting data, including textual, tabular, and graphical presentations. Tabular presentations include frequency distribution tables that are ungrouped, grouped, simple, and complete. Graphical presentations include bar charts, histograms, frequency polygons, pie charts, and pictographs to visually depict quantitative data using bars, rectangles, lines, circles, or pictures. The examples provided demonstrate how to construct different types of tables and graphs for a set of sample data.
Normal Distribution
This document discusses the normal distribution and related concepts. It begins with an introduction to the normal distribution and its properties. It then covers the probability density function and cumulative distribution function of the normal distribution. The rest of the document discusses key properties like the 68-95-99.7 rule, using the standard normal distribution, and how to determine if a data set follows a normal distribution including using a normal probability plot. Examples are provided throughout to illustrate the concepts.
Measures of Dispersion
If everything were the same, we would have no need of statistics. But, people's heights, ages, etc., do vary. We often need to measure the extent to which scores in a dataset differ from each other. Such a measure is called the dispersion of a distribution.
Graphical Representation of Data
Professor Sana Rehman, Assistant Professor, SCMS Pune talks all about GRAPHICAL REPRESENTATION OF DATA.
Contents:
1. Terminology
2. Qualitative and Quantitative Data
3. Continuous and Discrete Data
4. Primary and Secondary Data
5. Meaning of Statistics
6. Importance of the Organization of India
7. Arranging data in a sequence
8. Grouping and Tabulation of Data
9. Tally table
10. Histogram
11. Bar diagram or bar graph
12. Frequency Polygon
13. Cumulative Frequency Curve or Ogive
14.
Demography
Demography is the statistical study of human populations and encompasses the size, structure, and distribution of populations over time and space in response to births, deaths, and migration. Demographic data can be collected directly from vital records like censuses or birth/death records, or indirectly by surveying samples about topics like fertility rates. The scope of demography includes both macro-level trends like economic issues and population growth, as well as micro-level topics like individual families. A balanced view of demography encompasses factors like population size, composition, distribution, labor forces, and population policies.
Statistics-Measures of dispersions
This document discusses various measures of dispersion in statistics including range, mean deviation, variance, and standard deviation. It provides definitions and formulas for calculating each measure along with examples using both ungrouped and grouped frequency distribution data. Box-and-whisker plots are also introduced as a graphical method to display the five number summary of a data set including minimum, quartiles, and maximum values.
Measures of central tendency
- There are three main measures of central tendency: the mean, median, and mode. The mean is the average and is calculated by adding all values and dividing by the total number. The median is the middle value when data is arranged in order. The mode is the most frequently occurring value.
- To determine which measure to use, consider if the data has extreme values and whether the most common value is needed over the average. The mean can be skewed by outliers while the median and mode are more robust. The appropriate measure depends on the characteristics of the specific data set.
Normal distribution stat
1) The document discusses the characteristics and properties of the normal distribution, including that it is bell-shaped and symmetrical about the mean.
2) It defines z-values as a way to standardize normal distributions by transforming data values into standard scores based on the mean and standard deviation.
3) Examples are provided to demonstrate calculating probabilities using the standard normal distribution, such as finding the percentage of observations that fall within a certain number of standard deviations from the mean.
Normal Probability Distribution
The document discusses properties of normal distributions and the standard normal distribution. It provides examples of finding probabilities and values associated with normal distributions. The key points are:
- Normal distributions are continuous and bell-shaped. The mean, median and mode are equal.
- The standard normal distribution has a mean of 0 and standard deviation of 1.
- Probabilities under the normal curve can be found using z-scores and the standard normal table.
- Values like z-scores can be determined by finding the corresponding cumulative area in the standard normal table.
Measure of dispersion part I (Range, Quartile Deviation, Interquartile devi...
This tutorial gives the detailed explanation of "Measure of Dispersion" (Range, Quartile Deviation, Interquartile Range, Mean Deviation) with suitable illustrative example with MS Excel Commands of calculation in excel.
Population and demography
Population and demography are major areas of study for social scientists. A population is defined as a group of individuals occupying a particular place at a given time. Key factors in defining a population are group, place, and time. Population growth impacts issues like housing, food security, and the environment. Demography statistically analyzes population characteristics like size, composition by age and sex, birth and death rates, and immigration. Demographic data is important for policymaking and predicting future trends. Sources of demographic data include censuses, vital statistics like birth and death records, and surveys. Population change is influenced by fertility, mortality, and migration. Population pyramids display the age and sex structure of a population.
STATISTICS: Normal Distribution
The document provides an outline and explanation of key concepts related to the normal distribution. It begins with an introduction to probability distributions for continuous random variables and the definition of a density curve. It then defines terms and symbols used in the normal distribution, including mean, standard deviation, and z-scores. The document explains the characteristics of the normal distribution graphically and provides examples of finding areas under the normal curve using z-tables. It concludes with examples of finding unknown z-values and calculating probabilities for specific scenarios involving the normal distribution.
Vital statistics
The document discusses vital statistics, which are numerical records of life events like births, deaths, marriages, and divorces that can be used to study public health trends. Vital statistics are collected through civil registration systems and sample surveys. They provide data to evaluate health programs, plan for disease control, inform legislation and policymaking, and allow comparisons between populations. Important vital statistics include crude death rate, age-specific death rate, infant mortality rate, neonatal mortality rate, post-neonatal mortality rate, and maternal mortality rate.
Demography
Demography is the study of human populations focusing on population size, composition, and distribution. It deals with 5 demographic processes: fertility, mortality, marriage, migration, and social mobility. Demography can be static, focusing on population structure, or dynamic, focusing on changing patterns of mortality, fertility, and migration. India's population growth rate is the net of crude birth and death rates. India's population is young with 34.33% under 15 and growing elderly population above 60 years. Sex ratio is females per 1000 males and is adverse to women in India. Dependency ratio considers under 15 and over 65 as dependent on 15-64 age group. India's age pyramid is broad at the base and tapering at the top.
Normal distribution and sampling distribution
This document provides an overview of Chapter 5 from the textbook, which covers normal probability distributions. Section 5.1 introduces normal distributions and the standard normal distribution, including their key properties and how to interpret related graphs. It describes how any normal distribution can be transformed into a standard normal distribution for calculation purposes. Section 5.1 also shows how to find areas under the standard normal curve using the standard normal table. Section 5.2 discusses how to calculate probabilities for normally distributed variables by relating them to areas under the normal curve. It provides examples of finding probabilities and expected values.
Vital statistics and demography
This document provides an overview of vital statistics and demography. It defines vital statistics as data dealing with human mortality, morbidity and demography. Key sources of population data are identified as censuses, registration of vital events, sample registration surveys, and institutional records. Details are given on census taking methods, uses of censuses, census in Nepal, information collected in censuses, and measurement of population, mortality, fertility, and other demographic indicators.
Graphical presentation of data
Variables describe attributes that can vary between entities. They can be qualitative (categorical) or quantitative (numeric). Common types of variables include continuous, discrete, ordinal, and nominal variables. Data can be presented graphically through bar charts, pie charts, histograms, box plots, and scatter plots to better understand patterns and trends. Key measures used to summarize data include measures of central tendency (mean, median, mode) and measures of variability (range, standard deviation, interquartile range).
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Mans ciemats rudenī
- 1. Лива
- 4. Моя деревня расположена в красивом месте. Мы живем недалеко от реки Гауя. Oсеныю природа становится более красочнои, и я люблю это время. Осенью мы идем в школу, я рада встретиться со своими друзьями.