Chapter 2 Review Of The Literature Introduction Topic Subjec

Chapter 2review Of The Literatureintroduction Topic Subject Or Subj

Chapter 2 Review of the Literature Introduction • Topic – subject or subject matter of a study – e.g., “faculty teaching,†“organizational creativity,†“psychological stress†• Conduct literature review about the topic –Worth studying? – Scope? – Can be studied Creswell, Research Design 5e SAGE Publishing, 2018 3 The Research Topic • Gain insight into the topic by – Drafting a working title • “My study is about…†– Posing a brief question • What needs to be answered? Creswell, Research Design 5e SAGE Publishing, 2018 4 The Research Topic • First step is to examine research on the topic • How does this project contribute to the literature? • New topic, new elements, replication with new participants? Creswell, Research Design 5e SAGE Publishing, 2018 5 The Research Topic • The topic can be researched if – You have access to participants – You have resources to collect and analyze information • The topic should be researched if – The research will add to the literature about the topic – Scholars will be interested in the topic – A study of it will advance your personal goals Creswell, Research Design 5e SAGE Publishing, 2018 6 The Literature Review • Shares the results of other studies • Relates the study to the larger dialogue in the literature • Provides a framework for establishing the importance of the study • Provides a benchmark for comparing the results to other findings Creswell, Research Design 5e SAGE Publishing, 2018 7 The Literature Review The use of the literature: • Seek opinion of adviser or faculty members • Tell the reader you are aware of literature • Literature reviews take several forms: – Integrate what others have done and said – Criticize previous scholarly works – Bridge between related topics – Identify the central issues in the field Creswell, Research Design 5e SAGE Publishing, 2018 8 The Literature Review Creswell, Research Design 5e SAGE Publishing, 2018 9 The Literature Review The use of the literature: • In quantitative studies, researchers use literature to: – Provide direction to the research questions and hypotheses – Introduce a problem – Introduce and describe the theory that will be used – Examine the usefulness of the theory – Compare results with existing literature or predictions Creswell, Research Design 5e SAGE Publishing, The Literature Review The use of the literature: • In mixed methods studies, researchers use the literature: – In either a quantitative or qualitative approach – In each phase, consistent with either the quantitative or qualitative approach – Relative to the intended audience Creswell, Research Design 5e SAGE Publishing, The Literature Review Steps in conducting a literature review: • Identify key words • Search databases • Identify about 50 research reports in articles or books • Collect those that are central to your topic • Design a literature map • Draft summaries of relevant articles • Write a literature review, organizing it by important concepts Creswell, Research Design 5e SAGE Publishing, The Literature Review Searching computerized databases: • Computerized databases of the literature are available the Internet • Databases provide access to journal articles, conference papers and dissertations on a wealth of topics Creswell, Research Design 5e SAGE Publishing, The Literature Review Searching computerized databases: • Some of these online databases include: - ERIC - ProQuest - Sociological Abstracts - PsycINFO - Science Direct - Google scholar - - - EBSCO PubMed SSCI Creswell, Research Design 5e SAGE Publishing, The Literature Review Searching computerized databases: • Use both free databases and those available in your academic library • Search several databases, even those outside your field • Use guides to terms to locate articles • Locate articles close to your topic and use their terms in your search • Use databases that provide access to full text Creswell, Research Design 5e SAGE Publishing, The Literature Review A priority for selecting literature material: • Start with broad syntheses (such as encyclopedias) if you are new to the topic • Turn to journal articles in national journals – Best source for research reports • Next, consider books • Then examine conference papers • Scan for dissertations • Lastly, consider reports on the web Creswell, Research Design 5e SAGE Publishing, The Literature Review A literature map of the research • A literature map is a visual summary of existing research on a topic • The structure of the literature map may be: – Hierarchical pattern – Flowchart layout – Series of circles • Write a narrative description Creswell, Research Design 5e SAGE Publishing, The Literature Review Creswell, Research Design 5e SAGE Publishing, The Literature Review Abstracting studies: • Abstracts summarize major elements of the article • For research studies: – Mention the problem – State the central purpose – State information about the population and sample – Review key results – Point out methodological flaws (if a critique or methods review) Creswell, Research Design 5e SAGE Publishing, The Literature Review Abstracting studies: • For nonempirical studies (essays, opinions, etc.) – Mention the problem – Identify the central theme – State the major conclusions –Mention flaws in reasoning or logic (if a methodological review) Creswell, Research Design 5e SAGE Publishing, The Literature Review Creswell, Research Design 5e SAGE Publishing, The Literature Review Creswell, Research Design 5e SAGE Publishing, The Literature Review Style manuals: • Style manuals provide guidelines for producing scholarly work and include directions on: – Citing references in-text – End-of-text references – Creating headings – Footnotes (not used in all style manuals) – Presenting tables and figures • Reminder: Consistently use the chosen style manual Creswell, Research Design 5e SAGE Publishing, The Literature Review Definition of terms • Identify and define terms that readers need to understand a proposal • Define terms introduced in all sections of the research plan: – Title of the study – Problem statement – Purpose statement – Research questions, hypotheses, or objectives – Literature review – Theory base of the study – Methods section Creswell, Research Design 5e SAGE Publishing, The Literature Review Definition of terms • Qualitative studies – Inductive and evolutionary in nature – The definition of terms may appear later in the written report, perhaps in the data analysis • Quantitative studies – Deductive with a fixed set of objectives – All relevant terms are comprehensively defined earlier in the study Creswell, Research Design 5e SAGE Publishing, The Literature Review Definition of terms • Mixed methods studies – Follows the use of quantitative or qualitative approach – Clarify terms related to mixed methods Creswell, Research Design 5e SAGE Publishing, The Literature Review Definition of terms • Define terms when they first appear in the manuscript • Use specific operational definitions • Do not define terms using everyday language, be guided by the literature • Define terms so that they accomplish different goals • One may use a definition of terms section in the manuscript Creswell, Research Design 5e SAGE Publishing, The Literature Review Creswell, Research Design 5e SAGE Publishing, The Literature Review Creswell, Research Design 5e SAGE Publishing, The Literature Review Creswell, Research Design 5e SAGE Publishing, The Literature Review A quantitative or mixed methods literature review: • Introduce the review with a statement about the organization of the sections • Review literature about the independent variables • Review literature about the dependent variables • Review literature that relates the independent variables to the dependent variables Creswell, Research Design 5e 31 SAGE Publishing, 2018 The Literature Review A quantitative or mixed methods literature review: • Provide a summary – Highlight important studies – Capture major themes – Suggest why more research is needed – Advance how the proposed study will fill this need Creswell, Research Design 5e SAGE Publishing, Summary • Identify your topic through a brief title or central research question • Use the literature to – Present similar studies – Relate the study to the literature – Provide a framework for comparison • Different purpose depending on approach • Search databases using key terms Creswell, Research Design 5e SAGE Publishing, Line Graph 1) Generate a line graph to viualize your time-series data. Place the time intervals on the horizontal axis Time Index Quarter Sales 1 Q Q Q Q Q Q Q Q Q Q Q Q Q Q) How might you describe the TREND of the time-series? (upward or downward) 15 Q Sample response: Reading the graph from left to right, this time series looks as if the data is trending upward 16 Q Sales Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q Quarters Sales Trendline 3) Use Excel to add a trendline to the time-series chart. Select the trendline, change its color to one that is different from the graph, and thicken it Time Index Quarter Sales 1 Q Q Q Q Q Q Q Q Q Q Q Q Q Q) Upon visual inspection, which trendline appears to be most resprentative of the time-series data? 15 Q Sample Response: For this chart, the Moving Averages, with period 2, trend line appears to be most representative 16 Q Sales Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q Quarters Sales Exponential Smoothing 5) Use exponential smoothing (Data .. Data Analysis … Exponential Smoothing) to smooth out the peaks and vallies in the plot to better see the trend Time Index Quarter Sales Use dampening factors = .3, .6, and .9 to generate 3 charts 1 Q Q2 90 see image below 3 Q Q Q Q Q Q Q Q Q Q Q Q Q Q ExponentialSmoothing2 Time Index Quarter Sales 0.3 0.6 0. Q1 73 ERROR:#N/A ERROR:#N/A ERROR:#N/A 2 Q Q.9 79.8 74. Q... Q... Q... Q... Q... Q... Q... Q... Q... Q...) What happens in the chart as the dampening factor increases? 14 Q... Q...) Use of which dampening factor has best aided in your ability to see the time-series trend? Explain 16 Q... .3 dampening factor Actual Forecast #N/A 73 84.............. Time Point Sales .6 Dampening Factor Actual Forecast #N/A 73 79.8 96.28 96............ Time Point Sales .9 Dampening Factor Actual Forecast #N/A 73 74.7 79............. Time Point Sales Seasonality 8) Do you notice any SEASONAL effects? (predictable fluctuations (systematic) that occur during the same month (or quarters, etc ..)? Time Index Quarter Sales Explain. I so, use the line drawing tool to indicate this on your chart 1 Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Sample response: There appears to be a seasonal effect present in the graph. The graph fluctuates in a predictable pattern from quarter 1 to quarter 4 or yearly. Sales start low in quarter 1 and increases to a peak in Quarter 3 then decreases in Quarter 4 to near quarter 2 sales levels but not quite as low as sales posted for quarter 1. That is, it is expected that quarter 1 sales will be the lowest for the year and quarter 3 sales will be highest. Sales Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q Quarters Sales Forecast Sheet 9) Use Excel to Generate a Forecast sheet (Data … Forecast Menu … Forecast Sheet…Options) to predict values for the next 5 time intervals Use the Time Period colum for the Timeline Range window (see image below) Time Index Quarter Sales 1 Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q Enter the last Excel row number in your dataset Add 5 to your Forecast Start value Uncheck this box Time period column Measurement Data Forecast Sheet 2 Timeline Values Forecast ) List the next 5 values forecast .... Format this table to APA expectations . Timeline Forecast ..... Values Forecast ..... Moving Average Time Index Quarter Sales if there is no apparent trend, then smoothing with moving averages could be a next step to help identify the long term trend 1 Q1 73 used to reduce the random fluctuation 2 Q2 90 Simple moving average (SMA) is an arithmetic average of values at and near a particular time period - each observation is weighted equally 3 Q compute means for a sequence of L observed values 4 Q4 98 assumes observations which are nearby in time are also likely to be close in value 5 Q Q Q) Use Data … Data Analysis … Moving Average ) to generate a 3 and 5 time period moving average chart 8 Q (See image below) 9 Q Q Q Q Q Q Q Q Data Measured Moving average period (3 or 5) Check to generate chart Moving Average2 Time Index Quarter Sales 1 Q1 73 ERROR:#N/A ERROR:#N/A 2 Q2 90 ERROR:#N/A ERROR:#N/A 3 Q. ERROR:#N/A 4 Q ERROR:#N/A 5 Q. Q. Q Q.. Q.. Q.. Q. Q. Q..) Using visual inspection, discuss the differences in relation with the actual graph and the 3 and 5 period Moving Averages graphs 14 Q.. Q. Q. Quarter Moving Average Actual Forecast #N/A #N/A 94........ Time Points Sales 5 Quarter Moving Average Actual Forecast #N/A #N/A #N/A #N/A 90..2 99.8 108.2 121.2 116.6 112.8 117..8 Time Points Sales image1.png image2.png image3.png Sheet1 Date Average Temperature ................................................................................................................................37 Project 2 Use this Kaggle Dataset Directions : Respond to the prompts below. Follow the ‘Do Not’ and ‘Do’ instructions. DO NOT : · Upload your Excel workbook to Moodle · Copy and paste the Kaggle dataset into this document · Upload your work as a Word document in Moodle DO · Paste or type your responses directly into this document · Save your completed work as a PDF file · Upload your only your PDF file to Moodle We’ll assume that past patterns that may be present in the time-series dataset that you are assigned continue into the future. Directions 1. Review and Use the Time Series Excel Practice workbook, posted to Moodle, as your guide to investigate this time-series data. Please ensure your move through and apply all the steps on all worksheets , to the dataset that you have been assigned. Respond to each question or prompt. Copy and paste the prompt, and your response, into your submission document Format all tables and charts to APA formatting expectations to avoid formatting point loss. 1. Post your results to Moodle in PDF format. Your writeup should include each prompt presented in the Time-series Excel Practice workbook, the number of the prompt, your responses to the prompts, and all generated charts and tables. Enlarge your charts so that the dates on the horizontal axis lay flat. DO NOT submit the Kaggle time series subset data set to Moodle.

Paper For Above instruction

This paper provides a comprehensive review of literature related to time series analysis, focusing on the methodologies, interpretation, and applications of various forecasting techniques. Drawing from Creswell (2018) and established statistical practices, the discussion emphasizes the importance of understanding trends, seasonal effects, and smoothing methods, which are fundamental in predictive modeling. The primary objective is to highlight how literature supports the utilization of techniques such as trendlines, exponential smoothing, moving averages, and forecast sheets to analyze temporal data for practical and research purposes.

Introduction

The study of time series data is vital across multiple disciplines, including economics, finance, environmental science, and marketing. Analyzing data over time enables researchers and practitioners to identify patterns, predict future occurrences, and inform decision-making processes. The review begins with key concepts such as trends, seasonality, and smoothing techniques, which serve as the foundation for effective temporal data analysis. Creswell’s (2018) guidelines on systematic literature review processes underpin the analysis, setting the stage for evaluating various methodologies used in practice.

Review of Literature on Techniques for Time Series Analysis

Literature indicates that trend analysis is central to comprehending long-term movements in data. Visual inspection of line graphs, complemented by trendlines—whether linear, moving averages, or exponential—provides insights into whether a series exhibits upward, downward, or stable patterns. For example, Creswell (2018) emphasizes the importance of selecting the most representative trendline, often favoring moving averages with appropriate periods due to their ability to smooth data and reveal underlying signals amidst noise.

Exponential smoothing techniques are extensively discussed in scholarly work for their effectiveness in forecasting and trend detection. The literature highlights that dampening factors—commonly set at 0.3, 0.6, and 0.9—adjust the sensitivity of the model to recent observations, affecting how quickly forecasts adapt to changes. Creswell (2018) underscores that higher dampening factors tend to produce smoother results, which can mask short-term fluctuations but better capture overall trends.

Seasonality, another critical component in time series analysis, is documented widely in the literature. Recognizable seasonal effects—predictable fluctuations recurring in specific periods—are often identified visually through pattern recognition or statistically through autocorrelation functions. Creswell (2018) suggests that recognizing seasonal patterns enables more accurate forecasting by adjusting models to account for systematic yearly or quarterly fluctuations.

Smoothing techniques such as moving averages (simple, double, or triple) are also prevalent in scholarly discussions. These methods reduce the impact of random variations, clarifying the trend and seasonal components. Creswell (2018) notes that moving averages, particularly with varying periods (e.g., 3, 5), can be invaluable for identifying long-term patterns and for preliminary data exploration before applying more complex models.

Application of Literature in Practical Analysis

The literature informs the process of conducting a practical time series analysis, as reflected in the steps outlined for Excel-based techniques. These include generating line graphs, adding trendlines, applying exponential smoothing with different dampening factors, and developing forecast sheets. Creswell's (2018) methodology emphasizes selecting the appropriate smoothing parameters and visually inspecting forecast models to ensure their adequacy in capturing true data patterns.

Furthermore, the literature supports the use of moving averages to detect hidden long-term trends, particularly when data lack apparent trends or are noisy. The comparative analysis of 3-period versus 5-period moving averages, as documented in recent studies, demonstrates their effectiveness in balancing responsiveness and smoothing, which is critical for accurate forecasting and decision-making.

Conclusion

Overall, the reviewed literature affirms that effective time series analysis hinges on the appropriate application of smoothing techniques, trend detection models, and seasonal