With example describe the following terms.

INTRODUCTION

1. With example describe the following terms.

 (i) Statistics is the science of conducting studies to collect, organizes, summarize, analyze and draw conclusion from data.

Statistics is said to be a science because it follow all the scientific procedure in collecting data which is

·         Collecting data

·         Organize  data

·         Summarizing data

·         Analyze data

·         Drawing conclusion data

ii. Variables are the characteristics or attribute that can assume different value.

The following are types of variables which are;-

                     i.            Qualitative variables

                   ii.            Quantitative variables

Qualitative variable are the variable that can be placed into distinct categories according some characteristics or attribute

Also qualitative variables some times are variable that are not numerical. It describe data that fits into categories

For example eye, color blue blank green gender, religious, geographic location

Qualitative variables

Is the variable which can have some numerical value, for example height body temperature, population?

iii Data is the value that a variable can assume.

For example, data can not exist without variable for example Height, Weight etc

iv. Information; these refers to the data that have been fully collected and well arranged for further use in different projects. For example if the data in the census have been collected can not be reported to the government before been well arranged so we arrange the data that have been collected in order to get an information.

V. Sample; is a representative part or a single item from a large or a whole group?

For example 20 students are selected in the class of 130 students at Naliendele secondary school to participate in the debate with the fellow school mates. So the sample here is 20 students who have been choose to volunteer a debate instead of taking a whole class.

vi. Population; is the entire pool from which statistical sample is drawn. Or sometimes population can be a whole members of the group about which you want to draw conclusion

For example all Tanzanian citizens who are registered to vote in local government election in 24 November 2019 are 40,000,000. The population is total number of citizen who have been registered to vote.

2. Differentiate between data and information

The following are the difference between the data and information

Data	Information
Are the values that can be assumed by other variables?	Are the data collected and organized.
Is the first process which is used in research process which play significant role in statistical analysis.	Are data which is processed and transformed in such a way it become a useful to the user.
Data is an unsystematic fact or details about something	Is the systematic and filtered form of data which is useful
Data is simple text and number	Is processed and interpreteddata
Data is an organized form i.e. randomly collected facts and figures which are processed to draw conclusion.	Is an organized data. It presents data in a better way and gives meaning to it.
Data does not depend on information.	Does not exist without data.

3. Describe the different types of variables.

Variables; Refers to the characteristics as attribute that can assume different values.

For example of variables gender, the household income of the citizens who voted in the last presidents election the publishing category.

The following are the main types of variables

i. Quantitative variables

Are variables which have some numerical values? Sometimes it can be represented in numbers for Example; Age, height, weight and body temperature.

Quantitative variables are further classified into two groups.

Discrete and continuous variables.

Ø  Discrete data is information that can be categorized into a classification it is based on court. It is typically counted in while number like; 1, 2, 3, 4, 5, 6, 7. For example number of children family number of students in a classroom.

Ø  Continuous data is the data gathered through measurement like height of plant, weight, temperature.

Difference between Discrete and Continuous variables.

Discrete	Continuous
Countable.Example; Temperature, Height, weight.	Measurable.example; Number of children or students in the class room.
Nothing between.	Always something between.
Digital	Analog

ii. Qualitative variables are the variables that are not numerical it describe data that fits into categories. Forexample; Gender, religious, geographical location.

4. Describe the different types of statistics and give out their different if there is any

Statistics is the science of conducting studies to collect, organizes, summarise, analyse and draw conclusion from data.

The following are types of statistics which are;-

1. Discriptive statistics

2. Inferential statistics

i. Descriptive statistics; Is the type of statistics that deals with the collection, organization, summansation and presentation of data? Forexample the data set is 20

[2, 3, 4, 5, 6]

The mean is 4 [20/5]

Mode of the data set is the value appearing most often.

Median is the figure situated in the middle of the data sets.

ii.  Inferential statistics; Is the type of statistics which is consist of generalization from sample to population performing estimation and hypothesis test determine relation and hypothesis test determine relationship among variables and making prediction and also it used to draw conclusion. Forexample; the more who attended class likely you will receive higher grades.it is the attendance your grade will probably improve.

Difference between Descriptive and inferential statistics.

Descriptive	Inferential
Uses data to provide description of the population, either through numerical calculation, graph or table	Make inferences and production about a population based on sample of data taken from the population in the quantity.
We choose a group that we want to describe and then measure all subject into that group.	It defines the population and then devises a sampling plan that produces a representative sample.

5. Define data collection and explain all statistical data collection methods that you know

Data collection; is the process of gathering data and measuring information on variables of interest in an established systematic fashion that enables to answer stated research question, test, and hypothesis and evaluate outcome.

The following are methods of Data collection in a statistics which are;-

1.      Questionnaires; are survey instruments that are complete by the subjects. Questionnaires, like interviews, can contain short closed ended questions (multiple choice) or broad open ended questions. Questionnaires are used to collect data from a large group of subjects on a specific topic.

2.       Telephone Survey is the one of the survey method used in collecting data either from general population or from specific target population. Telephone numbers are utilized by training interviewers to conduct and their gathering information from possible responsible responded. Telephone surveys have an advantage over personal interview surveys in that they are less costly. and people may be more candid in their opinions since there is no face to face contact. And disadvantages of telephone some people in the population will not have phones or will not answer when the calls are made, not all people have a chance of being surveyed.

3.       Interviews; are used collect data from small group of subjects on broad range of topics. You can use structured or unstructured interviews. Structured interviews are comparable to a questionnaire, with the same questions in the same order fore each subject and with multiple choice answers. For unstructured interviews question s can give per subject and can depend on answers given on previous questions, there is no fixed set of possible answers.

6. Explain the importance of statistics in community development

The following are importance of statistics to community development which are;-

Statistics plays an important role in business. A successful businessman must be very quickly and accurate in decision making. He knows what his customers want; he should therefore know what to produce and sell and in what quantities. So statistics helps businessman to plan production according to the taste of the customers, and the quality of the products can also be checked more efficiently by using statistical methods. Thus, it can be seen that all business activities are based on statistical information.

Statistics plays an important role in banking. Banks make use of statistics for a number of purposes. They work on the principle that everyone who deposits their money with the banks does not withdraw it at the same time. The bank earns profits out of these deposits by lending it to others on interest. Bankers use statistical approaches based on probability to estimate the number of deposits and their claims for a certain day.

It help the government to know the number of the whole population in the community; as it known  that any developed community must have an appropriate total number of the community member who are catalyst of development in the community. So through statistics knowledge in the community it will be easy to know the number of people or died at a certain period and the number of people born at a same period so through these it will be easy to know the number of man power remaining and how those people going to perform developmental activities in the community.

Statistics also help the community to plan, progress monitoring and evaluation of development activities through knowing the total number of community member it make easy for the community to plan ho do they going to perform their developmental activities