02 penyajian data
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The document discusses various methods for graphically presenting qualitative and quantitative data, including: - Bar charts and pie charts to present qualitative data by class and frequency. - Frequency distribution tables that group quantitative data into mutually exclusive classes showing the number of observations in each. - Histograms where classes are on the x-axis, frequencies on the y-axis, and frequencies are represented by adjacent bars of varying heights. The document also provides steps for constructing a frequency distribution, including determining the number of classes, class width, class limits, and tallying data into classes.
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2.1 Part 1 - Frequency Distributions
This section expands on frequency distributions by discussing additional features: midpoints, which are the averages of class limits; relative frequency, which shows what portion of the data falls in each class; and cumulative frequency, which is the running total of all previous classes' frequencies. It provides an example calculating these values for a given
Classes
This document summarizes Chapter 2 of a statistics textbook. It covers descriptive statistics including frequency distributions, graphs of distributions, measures of central tendency, variation, and position. Section 2.1 discusses constructing frequency distributions and graphs including histograms, polygons, relative histograms, and ogives. Examples are provided to demonstrate how to construct these graphs from sample data on internet usage times. Key steps include determining class widths, limits, frequencies, midpoints, boundaries, and plotting the graphs.
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This presentation discusses frequency distribution graphs. It provides examples of constructing frequency distribution tables and calculating class midpoints and cumulative frequencies. The key graphs for representing frequency distributions are described as histograms, frequency polygons, and cumulative frequency curves for continuous or quantitative data. Bar charts, line graphs and pie charts are also introduced as options to display grouped or ungrouped categorical data. Examples of each type of graph are included.
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This document discusses frequency distribution and methods for presenting grouped data. It defines key terms like class interval, class frequency, and class midpoint. It also provides steps for constructing a frequency distribution, including determining the number of classes and class interval. Examples are given to illustrate a frequency distribution table, relative frequency distribution, and different types of graphs - histograms, frequency polygons, cumulative frequency curves, line graphs, bar charts and pie charts - that can be used to present grouped quantitative data.
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1. The document discusses different methods for presenting numerical data, including tables, graphs, and numerical techniques.
2. It provides examples of tabular data arranged in classes with frequencies, class marks, cumulative frequencies, and relative frequencies.
3. The document also describes histograms and bar graphs as ways to graphically display class data, with histograms using rectangle heights and bar graphs using points at the class midpoint and frequency coordinates.
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The document discusses various ways of summarizing and displaying quantitative data, including through frequency tables, relative frequency tables, and two-way frequency tables. It provides examples and definitions for key terms related to frequency tables such as class boundaries, class midpoints, class width, marginal frequencies, and conditional relative frequency. The document also discusses how frequency tables can be used to validate data, explore trends, compare data over time or between samples.
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The document provides instructions for organizing raw data into a frequency distribution table and describes different ways to represent the distribution graphically, including histograms, frequency polygons, and cumulative frequency curves. It explains how to calculate class intervals and frequencies from raw data and construct tables showing the distribution. It also discusses representing the same data through vertical bar graphs, line graphs connecting class points, and curves showing cumulative frequencies below given values.
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2.1 Part 1 - Frequency Distributions
This section expands on frequency distributions by discussing additional features: midpoints, which are the averages of class limits; relative frequency, which shows what portion of the data falls in each class; and cumulative frequency, which is the running total of all previous classes' frequencies. It provides an example calculating these values for a given
Classes
This document summarizes Chapter 2 of a statistics textbook. It covers descriptive statistics including frequency distributions, graphs of distributions, measures of central tendency, variation, and position. Section 2.1 discusses constructing frequency distributions and graphs including histograms, polygons, relative histograms, and ogives. Examples are provided to demonstrate how to construct these graphs from sample data on internet usage times. Key steps include determining class widths, limits, frequencies, midpoints, boundaries, and plotting the graphs.
frequency distribution & graphs
This presentation discusses frequency distribution graphs. It provides examples of constructing frequency distribution tables and calculating class midpoints and cumulative frequencies. The key graphs for representing frequency distributions are described as histograms, frequency polygons, and cumulative frequency curves for continuous or quantitative data. Bar charts, line graphs and pie charts are also introduced as options to display grouped or ungrouped categorical data. Examples of each type of graph are included.
Frequency distribution & graph
This document discusses frequency distribution and methods for presenting grouped data. It defines key terms like class interval, class frequency, and class midpoint. It also provides steps for constructing a frequency distribution, including determining the number of classes and class interval. Examples are given to illustrate a frequency distribution table, relative frequency distribution, and different types of graphs - histograms, frequency polygons, cumulative frequency curves, line graphs, bar charts and pie charts - that can be used to present grouped quantitative data.
PDU 207 Basic Statistics: Frequency Distribution
What is frequency distribution? How it helps us organizing data?
(Lecture slides mostly in Bahasa Indonesia)
Presentation of data
1. The document discusses different methods for presenting numerical data, including tables, graphs, and numerical techniques.
2. It provides examples of tabular data arranged in classes with frequencies, class marks, cumulative frequencies, and relative frequencies.
3. The document also describes histograms and bar graphs as ways to graphically display class data, with histograms using rectangle heights and bar graphs using points at the class midpoint and frequency coordinates.
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The document discusses various ways of summarizing and displaying quantitative data, including through frequency tables, relative frequency tables, and two-way frequency tables. It provides examples and definitions for key terms related to frequency tables such as class boundaries, class midpoints, class width, marginal frequencies, and conditional relative frequency. The document also discusses how frequency tables can be used to validate data, explore trends, compare data over time or between samples.
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The document provides instructions for organizing raw data into a frequency distribution table and describes different ways to represent the distribution graphically, including histograms, frequency polygons, and cumulative frequency curves. It explains how to calculate class intervals and frequencies from raw data and construct tables showing the distribution. It also discusses representing the same data through vertical bar graphs, line graphs connecting class points, and curves showing cumulative frequencies below given values.
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This document provides an overview of key concepts for describing data through frequency tables, distributions, and graphs. It defines important terms like frequency table, distribution, class, interval and discusses how to organize both qualitative and quantitative data. Guidelines for data collection are provided. Examples are given to demonstrate how to construct frequency tables and distributions and convert them to relative frequencies. Finally, different types of graphs for presenting frequency distributions are described, including histograms, polygons and cumulative distributions.
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This document provides an overview of frequency distributions and how to construct a frequency distribution table from a set of data. It discusses the key steps: 1) determining the range of the data, 2) choosing the number of classes, 3) calculating the class width, and 4) tallying the frequency of observations within each class interval to populate the table. Guidelines for constructing frequency tables are also outlined, such as using mutually exclusive and exhaustive class intervals of uniform width. An example of constructing a 7-class frequency table from a set of 50 observations is shown to demonstrate the process.
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This document provides information about frequency distributions and constructing frequency distribution tables. It defines a frequency distribution as a representation of data in a tabular format showing the number of observations within intervals. It then outlines the general process for constructing a frequency table which includes determining the range, number of classes, class width, and recording the frequencies in a table. An example is provided of constructing a frequency table from data on the ages of 50 men who died from gunfire using 7 classes. Guidelines for constructing frequency tables are also listed.
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This document provides an overview of key concepts for presenting data and constructing frequency distributions. It defines different methods for presenting data including textual, tabular, and graphical forms. Tabular methods include components like table headings and stubs. Graphical methods are shown like bar graphs, line graphs, and pie charts. Frequency distributions arrange data by class intervals and calculate frequencies. Terms are defined for range, class interval, and cumulative and relative frequency. Examples demonstrate how to construct frequency distributions and calculate cumulative and relative frequencies.
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This document discusses frequency distributions and methods for graphically presenting frequency distribution data. It defines a frequency distribution as a tabulation or grouping of data into categories showing the number of observations in each group. The document outlines the parts of a frequency table as class limits, class size, class boundaries, and class marks. It then provides steps for constructing a frequency distribution table from a set of data. Finally, it discusses histograms and frequency polygons as methods for graphically presenting frequency distribution data, and provides examples of how to construct these graphs in Excel.
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The document discusses the steps to construct a frequency distribution table (FDT):
1. Find the range and number of classes or intervals.
2. Estimate the class width and list the lower and upper class limits.
3. Tally the observations in each interval and record the frequencies.
It also describes how to calculate relative frequencies and cumulative frequencies to vary the FDT.
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This document discusses frequency distributions and how to construct them from raw data. It provides examples of creating stem-and-leaf displays, frequency tables, relative frequency tables, and cumulative frequency tables from various data sets. Key concepts covered include class width, class boundaries, tallying data, and calculating relative frequencies and percentages. Overall, the document serves as a tutorial on how to organize and summarize data using various types of frequency distributions.
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Report frequency distribution table
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The document provides steps for constructing a frequency table from a set of test score data: 1) Compute the range and class interval size, 2) Set up the table with class intervals, 3) Tally the observations in each interval and compute frequencies, 4) Compute cumulative and relative frequencies. An example is provided using 30 test scores ranging from 76 to 99 grouped into intervals of size 4.
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This document provides information about frequency distributions and constructing frequency distribution tables. It defines a frequency distribution as a representation of data in a tabular format showing the number of observations within intervals. It then outlines the general process for constructing a frequency table which includes determining the range, number of classes, class width, and recording the frequencies in a table. An example is provided of constructing a frequency table from data on the ages of 50 men who died from gunfire using 7 classes. Guidelines for constructing frequency tables are also listed.
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frequency distribution table
The document discusses the steps to construct a frequency distribution table (FDT):
1. Find the range and number of classes or intervals.
2. Estimate the class width and list the lower and upper class limits.
3. Tally the observations in each interval and record the frequencies.
It also describes how to calculate relative frequencies and cumulative frequencies to vary the FDT.
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This document discusses frequency distributions and how to construct them from raw data. It provides examples of creating stem-and-leaf displays, frequency tables, relative frequency tables, and cumulative frequency tables from various data sets. Key concepts covered include class width, class boundaries, tallying data, and calculating relative frequencies and percentages. Overall, the document serves as a tutorial on how to organize and summarize data using various types of frequency distributions.
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This is a handout which consists of the basic concepts/terms about Frequency Distribution Table. It also includes the ways on how to properly construct a Frequency Distribution Table.
Report frequency distribution table
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This document defines key terms and concepts related to frequency distributions and describes how to create a frequency distribution from a dataset. It explains how to find the range of data, calculate class intervals, and construct a frequency table. An example is provided showing these steps to create a frequency distribution for a sample dataset. The document also covers interpolation, which is determining percentiles for values not reported in the frequency table. Finally, it lists and defines several visual displays that can be used to depict a frequency distribution such as histograms, frequency polygons, ogives, and pie charts.
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frequency distribution table 3
This document discusses the preparation of frequency distribution tables for continuous data series. It provides examples and steps for creating a grouped frequency distribution table, including deciding the number of classes, determining the range and class interval, and obtaining the class limits and frequencies to summarize the distribution. An example is given using test marks from 60 students to demonstrate creating a table with 10 class intervals. The document also includes review questions to assess understanding of key concepts like discrete versus continuous frequency distributions, exclusive classification limits, and how the number of classes is determined.
Standard deviation
- A random sample is selected in a way that gives each item of the population an equal chance of being included. Random sampling is a scientific method for obtaining an unbiased sample.
- Raw data from samples is organized into frequency tables to summarize the data for analysis and presentation. The number of classes in a frequency distribution can vary but is generally between 6-30.
- Range, class interval, frequency, mean, standard deviation and other statistical concepts are defined and formulas are provided to calculate them from grouped or ungrouped data. Histograms can be used to graphically represent the organized frequency distribution data.
Group-4-Report-Frequency-Distribution.ppt
This document provides an overview of frequency distributions and how to organize and represent data using frequency tables, histograms, frequency polygons and ogives. It defines key terms like frequency distribution, categorical vs grouped frequency distributions, and parts of a frequency table. Guidelines for constructing frequency distributions are presented, along with an example of creating a grouped frequency distribution from a dataset. Finally, methods for visualizing data through graphs are described.
Utilization-of-assessment-data-assessmentinLearning1.pptx
The document discusses statistical concepts used in analyzing assessment data. It defines statistics as the science of collecting, organizing, summarizing, and interpreting data. Descriptive statistics are used to describe data through measures of central tendency like the mean, median, and mode, while inferential statistics make predictions about a larger data set based on a sample. The document outlines steps for constructing frequency distributions and calculating the mean, including determining class limits and sizes. Graphs like histograms and frequency polygons can be used to visually represent grouped assessment data.
G7- ORGANIZATION OF FREQUENCY TABLE.pptx
This is about organizing data in a frequency table for Grade 7. For educational purposes only
Lecture 1 - Overview.pptx
This document provides an overview of introductory statistics concepts including:
- Descriptive statistics such as frequency distributions, histograms, and measures of central tendency are used to summarize and present data.
- Inferential statistics such as estimation and hypothesis testing are used to draw conclusions about populations based on sample data.
- Data can be organized and presented through tables, graphs including bar charts, pie charts, and scatter plots.
central tendency
The document discusses various statistical concepts including descriptive statistics, measures of central tendency, and analyzing data distributions. It defines statistics, explains why statistics are important in education, and outlines different types of statistics including descriptive statistics. The document also covers topics such as calculating the mean, median, and mode of data sets, constructing frequency distributions and histograms, and identifying symmetrical and skewed data distributions.
Unit 02.pptx
This document discusses frequency distributions and graphical representations of data. It provides the following key points:
1. A frequency distribution table organizes data into classes with frequencies showing how many data points fall into each class. It includes the class limits, frequencies, class marks, relative frequencies, and cumulative frequencies.
2. Graphical representations of frequency distributions include the frequency histogram, frequency polygon, relative frequency histogram, and cumulative frequency ogive. These graphs provide visual analysis of the distribution of data.
3. An example constructs a frequency distribution for ages of participants with five classes and calculates the relevant values like class width, frequencies, class marks, relative frequencies, and cumulative frequencies.
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留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
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8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
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【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
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1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
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【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Learn SQL from basic queries to Advance queries
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
The Ipsos - AI - Monitor 2024 Report.pdf
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版制作【微信:41543339】【利兹贝克特大学毕业证(LeedsBeckett毕业证书)】【微信:41543339】《成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路）我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
毕业原版【微信:176555708】【(GWU,GW毕业证书)乔治·华盛顿大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Analysis insight about a Flyball dog competition team's performance
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
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02 penyajian data
- 2. GRAPHIC PRESENTATION OF QUALITATIVE DATA • Bar chart: a graph that shows qualitative classes on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are proportional to the heights of the bars. • Pie chart: a chart that shows the proportion or percentage that each class represents of the total number of frequencies.
- 3. MINUMAN FAVORIT RESPONDEN Beverage Number Cola-Plus 40 Coca-Cola 25 Pepsi 20 Lemon-Lime 15 0 10 20 30 40 50
- 4. TINGKAT PENDIDIKAN TERAKHIR PEKERJA DI PT “SUMBER MAKMUR” PENDIDIKAN TERAKHIR BANYAKNYA PEKERJA SD 35 SMP 80 SMU/SMK 153 D3 40 S1 15 S2 5 SD, 35 SMP, 80 SMU/SMK, 153 D3, 40 S1, 15 S2, 5
- 5. PRESENTATION OF QUANTITATIVE DATA • Frequency distribution table • Histogram • Frequency polygon • Cumulative frequency distribution • Cumulative frequency polygon
- 6. FREQUENCY DISTRIBUTION • a grouping of data into mutually exclusive classes showing the number of observations in each class.
- 7. Hasil sampling mengenai usia pengguna internet 50 7 30 42 32 47 36 27 15 41 16 26 37 30 31 53 11 29 36 20 31 43 30 19 45 26 22 41 30 48
- 8. Contoh 1: Usia Pengguna Internet (hasil sampling) No. Usia (tahun) Frekuensi 1 5 hingga15 2 2 15 hingga25 5 3 25 hingga 35 11 4 35 hingga 45 7 5 45 hingga 55 5
- 9. (alternatif) No. Usia (tahun) Frekuensi 1 5 -14 2 2 15 - 24 5 3 25 - 34 11 4 35 - 44 7 5 45 - 54 5
- 10. CONSTRUCTING FREQUENCY DISTRIBUTION • Decide on the number of classes. • Determine the class interval/class width. • Set the individual class limits. • Tally the data into the classes. • Count the numberof items in each class.
- 11. Menentukan banyak kelas • Banyaknya data = n = 30 • Carilah bilangan asli k sekecil-kecilnya sedemikian hingga 2k > 30 • Jawab: k = 5
- 12. Menentukan lebar kelas • H= 53 • L = 7 • i ≥ 9,2 • i = 10
- 13. Menetapkan batas-batas kelas • Total jangkauan = 5.10 = 50 • Jangkauan aktual = 46 • Kelonggaran = 50 – 46 = 4 • Kelonggaran/2 =4/2 = 2 • Batas bawah kelas pertama = 7 – 2 = 5 No. Usia (tahun) 1 5 hingga15 2 15 hingga25 3 25 hingga 35 4 35 hingga 45 5 45 hingga 55
- 14. Distribusi Frekuensi Relatif NO. USIA (TAHUN) FREKUENSI FREK. RELATIF 1 5 - 14 2 0,07 2 15 - 24 5 0,17 3 25 - 34 11 0,37 4 35 - 44 7 0,23 5 45 - 54 5 0,17 JUMLAH 30 1,00
- 15. HISTOGRAM • a graph in which the classes are marked on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are represented by the heights of the bars, and the bars are drawn adjacent to each other.