Time Series Analysis and ForecastingJosip Novak
I offer time series analysis and forecasting services to help businesses and researchers identify trends, detect seasonality, and make accurate forecasts based on historical data. By combining statistical time series techniques with machine learning algorithms, I provide data-driven insights that enhance decision-making and strategic planning. My expertise in psychometrics, advanced statistics, and machine learning, along with domain expertise in psychology, ensures dependable insights for your specific context and objectives.
What's included
Report (.html, .docx, .pdf)
A comprehensive, structured report detailing the time series analysis and forecasting process. It includes:
1. Problem Definition – A clear statement of the business or research problem. This section includes the objectives of the analysis, the time period being studied, the time unit, and the key variables involved in the analysis.
2. Data Preparation – Overview of the initial data quality assessment, including any cleaning, transformation, or normalization steps taken. This section also includes a description of any data preprocessing methods, such as handling missing values or outliers.
3. Methodology – Overview of the time series modeling techniques employed (e.g., ARIMA, Exponential Smoothing), including the rationale for choosing these methods. Also, an explanation of the statistical techniques used to assess model fit and accuracy (e.g., AIC, BIC, RMSE, etc.).
4. Results & Interpretation – Detailed presentation of the model outcomes, including forecasts, confidence intervals, and any identified trends or seasonality.
5. Validation & Forecast Accuracy – Explanation of how the model’s accuracy was validated (e.g., cross-validation, out-of-sample testing). Presentation of error metrics, such as RMSE or MAPE, to demonstrate how well the model performs in predicting unseen data.
6. Summary of Insights – A clear overview of the most important insights. This section will also highlight potential risks or opportunities based on the results.
The Prepared Dataset (.csv, .xlsx, etc.) (Optional)
If required, a cleaned and pre-processed version of the dataset will be delivered alongside the report. This dataset will be formatted for easy use and further analysis, including:
1. Data Cleaning – Any issues such as missing values, duplicates, or outliers will have been addressed to ensure the dataset is tidy.
2. Normalization & Transformation – If necessary, the variables will be scaled, normalized, or transformed to ensure consistency and compatibility with specific techniques.
3. Feature Engineering – Relevant new features/variables (if applicable) will be created to enhance the dataset’s usability for mining.
4. Format & Structure – The dataset will be provided in a clean, structured format (e.g., .csv, .xlsx) with clear labeling of variables and standardized data types for ease of use.
FAQs
Example work
Contact for pricing
Tags
Jupyter
Python
R
RStudio
Data Analyst
Data Scientist
Statistician
Service provided by
Josip Novak Vukovar, Croatia
- 2
- Followers
Time Series Analysis and ForecastingJosip Novak
Contact for pricing
Tags
Jupyter
Python
R
RStudio
Data Analyst
Data Scientist
Statistician
I offer time series analysis and forecasting services to help businesses and researchers identify trends, detect seasonality, and make accurate forecasts based on historical data. By combining statistical time series techniques with machine learning algorithms, I provide data-driven insights that enhance decision-making and strategic planning. My expertise in psychometrics, advanced statistics, and machine learning, along with domain expertise in psychology, ensures dependable insights for your specific context and objectives.
What's included
Report (.html, .docx, .pdf)
A comprehensive, structured report detailing the time series analysis and forecasting process. It includes:
1. Problem Definition – A clear statement of the business or research problem. This section includes the objectives of the analysis, the time period being studied, the time unit, and the key variables involved in the analysis.
2. Data Preparation – Overview of the initial data quality assessment, including any cleaning, transformation, or normalization steps taken. This section also includes a description of any data preprocessing methods, such as handling missing values or outliers.
3. Methodology – Overview of the time series modeling techniques employed (e.g., ARIMA, Exponential Smoothing), including the rationale for choosing these methods. Also, an explanation of the statistical techniques used to assess model fit and accuracy (e.g., AIC, BIC, RMSE, etc.).
4. Results & Interpretation – Detailed presentation of the model outcomes, including forecasts, confidence intervals, and any identified trends or seasonality.
5. Validation & Forecast Accuracy – Explanation of how the model’s accuracy was validated (e.g., cross-validation, out-of-sample testing). Presentation of error metrics, such as RMSE or MAPE, to demonstrate how well the model performs in predicting unseen data.
6. Summary of Insights – A clear overview of the most important insights. This section will also highlight potential risks or opportunities based on the results.
The Prepared Dataset (.csv, .xlsx, etc.) (Optional)
If required, a cleaned and pre-processed version of the dataset will be delivered alongside the report. This dataset will be formatted for easy use and further analysis, including:
1. Data Cleaning – Any issues such as missing values, duplicates, or outliers will have been addressed to ensure the dataset is tidy.
2. Normalization & Transformation – If necessary, the variables will be scaled, normalized, or transformed to ensure consistency and compatibility with specific techniques.
3. Feature Engineering – Relevant new features/variables (if applicable) will be created to enhance the dataset’s usability for mining.
4. Format & Structure – The dataset will be provided in a clean, structured format (e.g., .csv, .xlsx) with clear labeling of variables and standardized data types for ease of use.
FAQs
Example work
Contact for pricing