Your question is incomplete so although i dont know what experiments you did some general things to do is
1. Increase sample size: By increasing the sample size, the statistical power of the experiment increases, which makes it easier to detect differences between groups or conditions.
2. Use a control group: A control group is essential to reduce the impact of confounding variables and to validate the experimental design. The control group should be identical to the experimental group, except for the manipulated variable.
3. Randomize the assignment of subjects: Randomization helps eliminate bias and ensures that differences between groups are due to the manipulated variable and not due to pre-existing differences between subjects.
4. Blind the experiment: Blinding reduces the impact of bias by preventing experimenters and subjects from knowing which group they are in. This can be achieved through single-blind or double-blind procedures.
5. Replicate the experiment: Replication is crucial to ensure the reliability of the results. Ideally, experiments should be replicated by different researchers in different labs.
6. Use appropriate statistical analysis: Choosing the right statistical analysis is important to ensure the validity of the results. Statistical tests should be chosen based on the type of data collected and the research question.
7. Document all procedures: Documenting all procedures, including the experimental design, data collection methods, and statistical analysis, is essential for transparency and reproducibility.
Hope this applies to your experiment in anyways best of luck