The Coursera course on statistics is more than enough. The lecture topics are given below. I would say till lecture 15 is necessary for a beginner.
**Lecture Topics **

- Lecture 1: Experimental research
- Lecture 2: Correlational research
- Lecture 3: Variables and distributions
- Lecture 4: Summary statistics
- Lecture 5: Correlation
- Lecture 6: Measurement
- Lecture 7: Introduction to regression
- Lecture 8: Null Hypothesis Significance Tests (NHST)
- Lecture 9: Central limit theorem
- Lecture 10: Confidence intervals
- Lecture 11: Multiple regression
- Lecture 12: Multiple regression continued
- Lecture 13: Moderation
- Lecture 14: Mediation
- Lecture 15: Group comparisons (t-tests)
- Lecture 16: Group comparisons (ANOVA)
- Lecture 17: Factorial ANOVA
- Lecture 18: Repeated measures ANOVA
- Lecture 19: Chi-square
- Lecture 20 Binary logistic regression
- Lecture 21: Assumptions revisited (correlation and regression)
- Lecture 22: Generalized Linear Model
- Lecture 23: Assumptions revisited (t-tests and ANOVA)
- Lecture 24: Non-parametrics (Mann-Whitney U, Kruskal-Wallis)

You can find many more interesting resources specifically on my blog post here- How to acquire the “Essential Skill Set”?- the Self Starter way.

Read Pronojit Saha‘s answer to What are some important statistics concepts that a beginner in data science should know? on Quora

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