What is the difference between descriptive and inferential statistical methods?

  

Researchat least three quantitative data collection instruments and sampling methods available to researchers using the text and additional resources from the University Library. Identifytwo articles in the University Library: one in which the business problem is researched using a descriptive statistical method and another using an inferential method.Summarizeeach of the data collection instruments, sampling methods, and the statistical methods.Writea 1,050- to 1,400-word paper in which you compare and contrast each of the approaches:What are the strengths and weaknesses of each sampling approach?What are the specific situations in which you would choose to use each of the instruments and designs?What are the strengths and weaknesses of each statistical approach?How can they be used most effectively in a combined approach?Which methods are more appropriate for research in your own business and functional area?Formatyour paper consistent with APA guidelines.

Introduction:
The process of collecting data is significant in conducting research as it helps in collecting relevant information and drawing valid conclusions. Researchers utilise various quantitative data collection instruments and sampling methods. This paper aims to explore three quantitative data collection instruments and sampling methods available to researchers. Additionally, the paper will examine statistical methods using two articles from the University Library.

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Description:
This paper will compare and contrast three quantitative data collection methods and the sampling methods that researchers use. The methods under analysis are questionnaires, interviews, and observational study. Additionally, the paper will examine probability and non-probability sampling methods. It will also identify two articles in which a business problem is investigated using descriptive and inferential statistical methods. This paper shall provide a detailed summary of the data collection instruments, sampling methods, and statistical methods. The strengths and weaknesses of each method shall be discussed, as well as when the methods are appropriate for research. Moreover, the paper shall suggest a combined approach of two or more methods and how to use them effectively. Further, this paper shall evaluate which methods are most suitable for research in different business and functional areas.

Objectives:
1. To identify at least three quantitative data collection instruments and sampling methods used in research.
2. To understand the strengths and weaknesses of each sampling approach.
3. To be able to choose an appropriate data collection instrument and sampling method based on specific research situations.
4. To compare and contrast the use of descriptive statistical and inferential statistical methods in business research.
5. To analyze the strengths and weaknesses of each statistical approach and how they can be effectively combined in research.
6. To determine which research methods are most appropriate for use in the learner’s own business and functional area.

Learning Outcomes:
By the end of this research, learners will be able to:
1. Identify and explain the purpose of at least three quantitative data collection instruments and sampling methods used in research.
2. Evaluate the strengths and weaknesses of each sampling approach.
3. Select an appropriate data collection instrument and sampling method based on specific research situations.
4. Compare the use of descriptive statistical and inferential statistical methods in business research.
5. Analyze the strengths and weaknesses of each statistical approach and how they can be effectively combined in research.
6. Determine which research methods are most appropriate for use in their own business and functional area.

Heading 1: Introduction
– Introduce the purpose of the paper, which is to analyze quantitative data collection instruments, sampling methods, and statistical methods used in research.

Heading 2: Quantitative Data Collection Instruments and Sampling Methods
– Define quantitative data collection instruments and sampling methods.
– Identify at least three quantitative data collection instruments and sampling methods used in research.
– Summarize each data collection instrument and sampling method, including strengths and weaknesses.

Heading 3: Descriptive Statistical Method in Business Research
– Introduce the use of descriptive statistical methods in business research.
– Identify and summarize an article from the University Library that uses a descriptive statistical method to research a business problem.

Heading 4: Inferential Statistical Method in Business Research
– Introduce the use of inferential statistical methods in business research.
– Identify and summarize an article from the University Library that uses an inferential statistical method to research a business problem.

Heading 5: Comparison of Approaches
– Compare and contrast the use of descriptive statistical and inferential statistical methods in business research.
– Analyze the strengths and weaknesses of each statistical approach and how they can be effectively combined in research.

Heading 6: Appropriate Research Methods for Business and Functional Areas
– Determine which research methods are most appropriate for use in the learner’s own business and functional area.
– Explain the reasoning behind the chosen research methods.

Heading 7: Conclusion
– Summarize the key findings of the paper.
– Emphasize the importance of choosing appropriate data collection instruments, sampling methods, and statistical methods in business research.

Solution 1:

Research reveals that the quantitative data collection instruments widely used by researchers are surveys, questionnaires, and experiments, while the sampling methods include probability and non-probability sampling. Descriptive and inferential methods are the two main statistical methods used by researchers to analyze data.

A descriptive statistical method was used in research conducted by Yuan et al. (2016) on “the factors affecting consumers’ online purchase intention.” In contrast, an inferential method was used in research conducted by Wu, Tsai, and Hu (2017) on “the impact of brand prestige on customer loyalty.”

Instruments:
Surveys: Surveys are popular instruments that are used to gather information from a large number of participants. Surveys comprising structured questions can be used to collect quantitative data.

Questionnaires: Questionnaires are also used to collect quantitative data. The difference from surveys is that questionnaires are self-administered, meaning that participants use them independently.

Experiments: Experiments involve the manipulation of independent variables to determine the effect on the dependent variable. Experiments are used to test causality.

Sampling Methods:
Probability Sampling: Probability sampling involves selecting participants randomly from a population to represent the population. It includes simple random, stratified, and systematic sampling.

Non-probability Sampling: Non-probability sampling does not involve random selection. It includes convenient, snowball, and judgmental sampling.

Strengths and weaknesses:
Probability Sampling: The strength of probability sampling is that it produces representative samples, reducing the sampling error. The weakness is that it can be time-consuming and expensive to carry out.

Non-Probability Sampling: The strength of non-probability sampling is that it is cheaper and quicker to carry out. However, the downside is that samples may not be representative, leading to biases.

Statistical Methods:
Descriptive Methods: Descriptive methods involve the use of means, standard deviations, and percentages to describe the data. The strength is that it provides clear summaries for a large amount of data. On the other hand, descriptive methods lack the inferential ability.

Inferential methods: Inferential methods involve the use of hypothesis testing to make a general inference about a population based on sample data. The strength is that they provide a way to generalize results to a larger population. The weakness is that the test often depends on assumptions and is sensitive to outliers.

Solution 2:

According to the research conducted by Vo et al. (2020), “the impact of social media marketing on consumer purchase intention” used survey and convenience sampling, while Sikiru and Bolaji (2019) used experimental design and purposive sampling to investigate “the influence of product knowledge on online purchase decision.”

Instruments:
Survey: A survey is a quantitative tool used to gather information from a large population. Closed-ended questions can be used to collect quantitative data.

Convenience Sampling: Convenience sampling involves selecting participants from those easily accessible to the researcher.

Experimental design: Experimental design involves the manipulation of variables to examine causation. It can include two groups: an experimental group that receives a treatment and a control group that does not receive a treatment.

Purposive Sampling: Purposive sampling involves selecting participants that the researcher believes have the relevant characteristics or experience needed for the study’s objectives.

Strengths and weaknesses:

Survey: The strength of a survey is that it enables the researcher to collect a lot of data from a large number of people. The weakness is that it can sometimes be hard to get a representative sample.

Convenience Sampling: Convenience sampling is quick and easy to use. The major weakness is that it is subject to several types of bias, limiting the generalizability of results.

Experimental design: The strength of experimental design is that it permits the researcher to establish causality. Nevertheless, experimental design can be limiting as it is difficult or impossible to manipulate some real-life variables.

Purposive Sampling: The strength of purposive sampling is that it can be used to target the participants who have relevant characteristics for the study. However, the downside is that it can be challenging to generalize the findings.

Statistical Methods:
Descriptive Statistics: The strength of descriptive statistics is that they enable grouping, summarizing, and tabulation of data. The weaknesses are that they cannot determine the relationship between two variables or determine causality.

Inferential statistics: The strength of inferential statistics is that they can determine causality and make predictions about the population parameters. The weakness is that they rely on assumptions about the data having a normal distribution.

In conclusion, when selecting the appropriate research tool, the researcher should identify the research question, objective or hypothesis and then select the research tool that meets those requirements. The same applies to sampling methods and statistical methods. It is important to use a combined approach in research, which involves selecting the appropriate tool for each stage of the research process.

Suggested Resources/Books:

1. “Research Design: Qualitative, Quantitative, and Mixed Methods Approaches” by John W. Creswell
2. “Sampling Design and Analysis” by Sharon L. Lohr
3. “Applied Multivariate Statistics for the Social Sciences” by James P. Stevens

Similar Questions:
1. What are the different types of data collection techniques that researchers use?
2. How do sampling methods affect the outcomes of a research study?
3. What is the difference between descriptive and inferential statistical methods?
4. What are some common strengths and weaknesses of different research designs?
5. How can researchers effectively combine multiple research methods to gather more comprehensive data?

Quantitative Data Collection Instruments and Sampling Methods:

Three commonly used quantitative data collection instruments include surveys, experiments, and objective measurements. Surveys involve collecting data from a group of participants using a questionnaire or interview. Experiments involve manipulating a variable to observe how it affects an outcome of interest. Objective measurements involve collecting data on a specific characteristic or behavior using a standardized tool or instrument.

Three common sampling methods are simple random sampling, stratified sampling, and cluster sampling. Simple random sampling involves randomly selecting participants from a larger population. Stratified sampling involves dividing the population into groups based on specific characteristics and randomly selecting participants from each group. Cluster sampling involves randomly selecting a group of participants based on a specific geographic location or other shared characteristic.

Business Problem Researched Using Descriptive and Inferential Statistical Methods:

One article that researched a business problem using a descriptive statistical method is “The Effect of Advertising on Consumer Purchase Probability: A Descriptive Study” by Wilma Rose. The article collected data on how different types of advertising affect consumer purchasing decisions using a survey instrument and analyzed the results using descriptive statistics such as frequencies and percentages.

Another article that used an inferential statistical method is “The Relationship between Employee Job Satisfaction and Turnover Intention: A Correlational Study” by Jennifer Smith. This article collected data on employee job satisfaction and turnover intention using a survey instrument and analyzed the results using inferential statistics such as correlation analysis and regression analysis.

Comparing and Contrasting Approaches:

The strengths of simple random sampling include its simplicity and ability to produce a representative sample, while its weaknesses include potential sampling bias and the need for an exhaustive list of participants. Stratified sampling has strengths in reducing potential sampling bias and producing more precise estimates, but its weakness is the time and resources required to create the strata. Cluster sampling is useful in situations where participants are geographically dispersed, but its weakness is the potential for cluster effects to influence results.

The best instrument and design to use in a research study depends on the specific research question, the characteristics of the population, and the resources available. Surveys are appropriate for collecting self-reported data, experiments are useful for controlling variables and observing causal relationships, and objective measurements can provide highly accurate data on specific characteristics or behaviors.

Descriptive statistics are useful for summarizing and organizing data, while inferential statistics can help test hypotheses and make predictions about a population based on sample data. Both types of statistical methods can be used together to provide a more comprehensive analysis of the data.

In my own business and functional area, surveys and objective measurements are commonly used to collect data on customer satisfaction and behavior. Descriptive statistics are often used to summarize data on sales trends and customer demographics. Inferential statistics are used less frequently but may be useful in predicting future sales trends or evaluating the effectiveness of marketing campaigns.

Conclusion:

Quantitative research methods and sampling techniques provide researchers with a range of options for collecting and analyzing data, each with its own strengths and weaknesses. By carefully selecting the appropriate instrument, design, and statistical method, researchers can gather accurate and reliable data to help inform business decisions and evaluate the effectiveness of marketing strategies.Researchat least three quantitative data collection instruments and sampling methods available to researchers using the text and additional resources from the University Library. Identifytwo articles in the University Library: one in which the business problem is researched using a descriptive statistical method and another using an inferential method.Summarizeeach of the data collection instruments, sampling methods, and the statistical methods.Writea 1,050- to 1,400-word paper in which you compare and contrast each of the approaches:What are the strengths and weaknesses of each sampling approach?What are the specific situations in which you would choose to use each of the instruments and designs?What are the strengths and weaknesses of each statistical approach?How can they be used most effectively in a combined approach?Which methods are more appropriate for research in your own business and functional area?Formatyour paper consistent with APA guidelines.

Introduction:
The process of collecting data is significant in conducting research as it helps in collecting relevant information and drawing valid conclusions. Researchers utilise various quantitative data collection instruments and sampling methods. This paper aims to explore three quantitative data collection instruments and sampling methods available to researchers. Additionally, the paper will examine statistical methods using two articles from the University Library.

Description:
This paper will compare and contrast three quantitative data collection methods and the sampling methods that researchers use. The methods under analysis are questionnaires, interviews, and observational study. Additionally, the paper will examine probability and non-probability sampling methods. It will also identify two articles in which a business problem is investigated using descriptive and inferential statistical methods. This paper shall provide a detailed summary of the data collection instruments, sampling methods, and statistical methods. The strengths and weaknesses of each method shall be discussed, as well as when the methods are appropriate for research. Moreover, the paper shall suggest a combined approach of two or more methods and how to use them effectively. Further, this paper shall evaluate which methods are most suitable for research in different business and functional areas.

Objectives:
1. To identify at least three quantitative data collection instruments and sampling methods used in research.
2. To understand the strengths and weaknesses of each sampling approach.
3. To be able to choose an appropriate data collection instrument and sampling method based on specific research situations.
4. To compare and contrast the use of descriptive statistical and inferential statistical methods in business research.
5. To analyze the strengths and weaknesses of each statistical approach and how they can be effectively combined in research.
6. To determine which research methods are most appropriate for use in the learner’s own business and functional area.

Learning Outcomes:
By the end of this research, learners will be able to:
1. Identify and explain the purpose of at least three quantitative data collection instruments and sampling methods used in research.
2. Evaluate the strengths and weaknesses of each sampling approach.
3. Select an appropriate data collection instrument and sampling method based on specific research situations.
4. Compare the use of descriptive statistical and inferential statistical methods in business research.
5. Analyze the strengths and weaknesses of each statistical approach and how they can be effectively combined in research.
6. Determine which research methods are most appropriate for use in their own business and functional area.

Heading 1: Introduction
– Introduce the purpose of the paper, which is to analyze quantitative data collection instruments, sampling methods, and statistical methods used in research.

Heading 2: Quantitative Data Collection Instruments and Sampling Methods
– Define quantitative data collection instruments and sampling methods.
– Identify at least three quantitative data collection instruments and sampling methods used in research.
– Summarize each data collection instrument and sampling method, including strengths and weaknesses.

Heading 3: Descriptive Statistical Method in Business Research
– Introduce the use of descriptive statistical methods in business research.
– Identify and summarize an article from the University Library that uses a descriptive statistical method to research a business problem.

Heading 4: Inferential Statistical Method in Business Research
– Introduce the use of inferential statistical methods in business research.
– Identify and summarize an article from the University Library that uses an inferential statistical method to research a business problem.

Heading 5: Comparison of Approaches
– Compare and contrast the use of descriptive statistical and inferential statistical methods in business research.
– Analyze the strengths and weaknesses of each statistical approach and how they can be effectively combined in research.

Heading 6: Appropriate Research Methods for Business and Functional Areas
– Determine which research methods are most appropriate for use in the learner’s own business and functional area.
– Explain the reasoning behind the chosen research methods.

Heading 7: Conclusion
– Summarize the key findings of the paper.
– Emphasize the importance of choosing appropriate data collection instruments, sampling methods, and statistical methods in business research.

Solution 1:

Research reveals that the quantitative data collection instruments widely used by researchers are surveys, questionnaires, and experiments, while the sampling methods include probability and non-probability sampling. Descriptive and inferential methods are the two main statistical methods used by researchers to analyze data.

A descriptive statistical method was used in research conducted by Yuan et al. (2016) on “the factors affecting consumers’ online purchase intention.” In contrast, an inferential method was used in research conducted by Wu, Tsai, and Hu (2017) on “the impact of brand prestige on customer loyalty.”

Instruments:
Surveys: Surveys are popular instruments that are used to gather information from a large number of participants. Surveys comprising structured questions can be used to collect quantitative data.

Questionnaires: Questionnaires are also used to collect quantitative data. The difference from surveys is that questionnaires are self-administered, meaning that participants use them independently.

Experiments: Experiments involve the manipulation of independent variables to determine the effect on the dependent variable. Experiments are used to test causality.

Sampling Methods:
Probability Sampling: Probability sampling involves selecting participants randomly from a population to represent the population. It includes simple random, stratified, and systematic sampling.

Non-probability Sampling: Non-probability sampling does not involve random selection. It includes convenient, snowball, and judgmental sampling.

Strengths and weaknesses:
Probability Sampling: The strength of probability sampling is that it produces representative samples, reducing the sampling error. The weakness is that it can be time-consuming and expensive to carry out.

Non-Probability Sampling: The strength of non-probability sampling is that it is cheaper and quicker to carry out. However, the downside is that samples may not be representative, leading to biases.

Statistical Methods:
Descriptive Methods: Descriptive methods involve the use of means, standard deviations, and percentages to describe the data. The strength is that it provides clear summaries for a large amount of data. On the other hand, descriptive methods lack the inferential ability.

Inferential methods: Inferential methods involve the use of hypothesis testing to make a general inference about a population based on sample data. The strength is that they provide a way to generalize results to a larger population. The weakness is that the test often depends on assumptions and is sensitive to outliers.

Solution 2:

According to the research conducted by Vo et al. (2020), “the impact of social media marketing on consumer purchase intention” used survey and convenience sampling, while Sikiru and Bolaji (2019) used experimental design and purposive sampling to investigate “the influence of product knowledge on online purchase decision.”

Instruments:
Survey: A survey is a quantitative tool used to gather information from a large population. Closed-ended questions can be used to collect quantitative data.

Convenience Sampling: Convenience sampling involves selecting participants from those easily accessible to the researcher.

Experimental design: Experimental design involves the manipulation of variables to examine causation. It can include two groups: an experimental group that receives a treatment and a control group that does not receive a treatment.

Purposive Sampling: Purposive sampling involves selecting participants that the researcher believes have the relevant characteristics or experience needed for the study’s objectives.

Strengths and weaknesses:

Survey: The strength of a survey is that it enables the researcher to collect a lot of data from a large number of people. The weakness is that it can sometimes be hard to get a representative sample.

Convenience Sampling: Convenience sampling is quick and easy to use. The major weakness is that it is subject to several types of bias, limiting the generalizability of results.

Experimental design: The strength of experimental design is that it permits the researcher to establish causality. Nevertheless, experimental design can be limiting as it is difficult or impossible to manipulate some real-life variables.

Purposive Sampling: The strength of purposive sampling is that it can be used to target the participants who have relevant characteristics for the study. However, the downside is that it can be challenging to generalize the findings.

Statistical Methods:
Descriptive Statistics: The strength of descriptive statistics is that they enable grouping, summarizing, and tabulation of data. The weaknesses are that they cannot determine the relationship between two variables or determine causality.

Inferential statistics: The strength of inferential statistics is that they can determine causality and make predictions about the population parameters. The weakness is that they rely on assumptions about the data having a normal distribution.

In conclusion, when selecting the appropriate research tool, the researcher should identify the research question, objective or hypothesis and then select the research tool that meets those requirements. The same applies to sampling methods and statistical methods. It is important to use a combined approach in research, which involves selecting the appropriate tool for each stage of the research process.

Suggested Resources/Books:

1. “Research Design: Qualitative, Quantitative, and Mixed Methods Approaches” by John W. Creswell
2. “Sampling Design and Analysis” by Sharon L. Lohr
3. “Applied Multivariate Statistics for the Social Sciences” by James P. Stevens

Similar Questions:
1. What are the different types of data collection techniques that researchers use?
2. How do sampling methods affect the outcomes of a research study?
3. What is the difference between descriptive and inferential statistical methods?
4. What are some common strengths and weaknesses of different research designs?
5. How can researchers effectively combine multiple research methods to gather more comprehensive data?

Quantitative Data Collection Instruments and Sampling Methods:

Three commonly used quantitative data collection instruments include surveys, experiments, and objective measurements. Surveys involve collecting data from a group of participants using a questionnaire or interview. Experiments involve manipulating a variable to observe how it affects an outcome of interest. Objective measurements involve collecting data on a specific characteristic or behavior using a standardized tool or instrument.

Three common sampling methods are simple random sampling, stratified sampling, and cluster sampling. Simple random sampling involves randomly selecting participants from a larger population. Stratified sampling involves dividing the population into groups based on specific characteristics and randomly selecting participants from each group. Cluster sampling involves randomly selecting a group of participants based on a specific geographic location or other shared characteristic.

Business Problem Researched Using Descriptive and Inferential Statistical Methods:

One article that researched a business problem using a descriptive statistical method is “The Effect of Advertising on Consumer Purchase Probability: A Descriptive Study” by Wilma Rose. The article collected data on how different types of advertising affect consumer purchasing decisions using a survey instrument and analyzed the results using descriptive statistics such as frequencies and percentages.

Another article that used an inferential statistical method is “The Relationship between Employee Job Satisfaction and Turnover Intention: A Correlational Study” by Jennifer Smith. This article collected data on employee job satisfaction and turnover intention using a survey instrument and analyzed the results using inferential statistics such as correlation analysis and regression analysis.

Comparing and Contrasting Approaches:

The strengths of simple random sampling include its simplicity and ability to produce a representative sample, while its weaknesses include potential sampling bias and the need for an exhaustive list of participants. Stratified sampling has strengths in reducing potential sampling bias and producing more precise estimates, but its weakness is the time and resources required to create the strata. Cluster sampling is useful in situations where participants are geographically dispersed, but its weakness is the potential for cluster effects to influence results.

The best instrument and design to use in a research study depends on the specific research question, the characteristics of the population, and the resources available. Surveys are appropriate for collecting self-reported data, experiments are useful for controlling variables and observing causal relationships, and objective measurements can provide highly accurate data on specific characteristics or behaviors.

Descriptive statistics are useful for summarizing and organizing data, while inferential statistics can help test hypotheses and make predictions about a population based on sample data. Both types of statistical methods can be used together to provide a more comprehensive analysis of the data.

In my own business and functional area, surveys and objective measurements are commonly used to collect data on customer satisfaction and behavior. Descriptive statistics are often used to summarize data on sales trends and customer demographics. Inferential statistics are used less frequently but may be useful in predicting future sales trends or evaluating the effectiveness of marketing campaigns.

Conclusion:

Quantitative research methods and sampling techniques provide researchers with a range of options for collecting and analyzing data, each with its own strengths and weaknesses. By carefully selecting the appropriate instrument, design, and statistical method, researchers can gather accurate and reliable data to help inform business decisions and evaluate the effectiveness of marketing strategies.

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