1. In addition, some machine learning algorithms can be used to detect the authenticity of data, such as anomaly detection algorithm and clustering analysis algorithm. Finally, scientists can also verify the authenticity of the data through some experiments.

2, the paper data fraud can be seen. Graduation thesis checks the repetition ratio of your thesis and other papers in the database, and usually does not check the authenticity of the data.

3. Enter the URL (/) of the duplicate checking system in the browser. After entering the duplicate checking homepage, select the appropriate duplicate checking system at the bottom of the homepage. Enter the title and author of the paper in the duplicate checking interface, upload the paper to the duplicate checking system, and click the submit test button.

4. We can find that the fund papers are fraudulent by checking the weight of HowNet.

5. Whether the second data, structure and logic are reasonable: The biggest difference between real papers and fake papers is that the results of real research are uncertain, while fake papers are written after a certain result, which will cause a phenomenon, and the overall structure of fake papers will often be perfect.

6. The falsification of the questionnaire data of undergraduate graduation thesis will lead to the risk of being discovered, which belongs to academic misconduct. The details are as follows: academic data fraud: research data obtained on the basis of fraud, no matter how reasonable and meticulous, will inevitably be discovered. What are the chances? It depends on luck.

How was the falsification of multiple linear regression data discovered?

1.t test is used to test the correctness of the hypothesis of parameter significance. The factors affecting variables are all significant linear regression, which is used to get the linear relationship between two variables. Multiple linear regression is an extension of linear regression, which is used to analyze the relationship between one variable and multiple variables.

2. There is no random error in the selected value: this assumption is almost impossible to satisfy. The existence of measurement error will reduce the accuracy of prediction and affect the estimation of error variance, negative correlation coefficient and single regression coefficient.

3. yes. The purpose and significance of data regression analysis is to fit a series of influencing factors and results into an equation, and then apply this equation to other similar events to make predictions.

4. Basic assumptions of simple linear regression model: ① Zero mean hypothesis; ② Homovariance hypothesis; ③ No autocorrelation hypothesis; ④ It is assumed that the random disturbance term has nothing to do with explanatory variables; ⑤ Normal hypothesis.

How to see the falsification of stata empirical data?

1, open the software and create a new table in the welcome interface &; Select column → enterandploterrorvalues all readycalculedelsewhere → mean, SD, N→Create in the graphic box to create and enter a data table.

2. Open Stata 10 software, click the "File" option in the upper left corner, and then select "Import". Click the "Import" option, and then select the "Excelspreadsheet" option. In the newly popped-up "importExcel" interface, click the "browser" option in the upper right corner to load the panel data.

3.reg only provides regression analysis. In the results, each variable is followed by a p value, where P=0 represents significance, and below P=0.0 1, the significance level is 1%, 0.05 is 5%, and 0. 1 is 10%. If you want a t value, you can use ttestA and so on.

4.stata is not significant, mainly depending on the P value. Reg only provides regression analysis. In the result, each variable is followed by a column with a value of p, that is, p | t |, where P=0 represents significance. In addition, it depends on your importance. If the significance level is set to 5%, all variables with p value less than 0.05 are significant.

How do you know if there is fraud by providing raw data?

Detection method: observe whether the trading volume of the stock conforms to its price fluctuation. If the turnover suddenly increases or decreases, but the price does not fluctuate accordingly, there may be fraud. Analyze whether the trading volume of stocks is consistent with the number of transactions.

Open the software and create a new table in the welcome interface &; Select column → enterandploterrorvalues all readycalculedelsewhere → mean, SD, N→Create in the graphic box to create and enter a data table.

As long as it is false, there will definitely be clues, and if you look closely, you will definitely find out. For example, although the collection records have been modified in the database, from the point of view of the software system, problems can no longer be found, but there are still physical bills and accounts to check. So, in a word, the fake is definitely not true.

If the reviewer has doubts about the authenticity of the data, he will ask the author to provide the original data. Some journals require authors to provide original data when submitting articles. Some reviewers will do it again according to your theory. If it is found out that it is academic fraud, it will be dealt with seriously according to the method of dealing with the falsification of dissertations.

First: If you can determine the time when the data was exported, then look at the time when the file was later modified. If the file is modified later, it may be the result of modification. Second, it is difficult to falsify the data in the instrument. It can be re-exported by the instrument for inspection.